{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:56:33Z","timestamp":1777384593197,"version":"3.51.4"},"reference-count":189,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T00:00:00Z","timestamp":1626393600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T00:00:00Z","timestamp":1626393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","award":["2016-05673"],"award-info":[{"award-number":["2016-05673"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN Oper. Res. Forum"],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1007\/s43069-021-00068-x","type":"journal-article","created":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T13:02:48Z","timestamp":1637240568000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Review on Nature-Inspired Algorithms"],"prefix":"10.1007","volume":"2","author":[{"given":"Wael","family":"Korani","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7381-1064","authenticated-orcid":false,"given":"Malek","family":"Mouhoub","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,16]]},"reference":[{"key":"68_CR1","doi-asserted-by":"crossref","unstructured":"Rao SS (2009)\u00a0Engineering optimization: theory and practice. John Wiley & Sons","DOI":"10.1002\/9780470549124"},{"key":"68_CR2","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.ins.2013.02.041","volume":"237","author":"I Boussa\u00efd","year":"2013","unstructured":"Boussa\u00efd I, Lepagnot J, Siarry P (2013) A survey on optimization metaheuristics. Inf Sci 237:82\u2013117","journal-title":"Inf Sci"},{"key":"68_CR3","volume-title":"Artificial intelligence through simulated evolution","author":"LJ Fogel","year":"1966","unstructured":"Fogel LJ, Owens AJ, Walsh MJ (1966) Artificial intelligence through simulated evolution. Wiley, Chichester, WS, UK"},{"key":"68_CR4","unstructured":"Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence"},{"issue":"4598","key":"68_CR5","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671\u2013680","journal-title":"Science"},{"key":"68_CR6","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In Proc IEEE Intl Con on Neural Networks (Perth, Australia). pp.\u00a01942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"68_CR7","doi-asserted-by":"crossref","unstructured":"Passino KM (2002) Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst\u00a022(3):52\u201367","DOI":"10.1109\/MCS.2002.1004010"},{"key":"68_CR8","doi-asserted-by":"crossref","unstructured":"Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In 2007 IEEE congress on evolutionary computation.\u00a0pp. 4661\u20134667","DOI":"10.1109\/CEC.2007.4425083"},{"issue":"2","key":"68_CR9","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TCYB.2014.2322602","volume":"45","author":"R Cheng","year":"2014","unstructured":"Cheng R, Jin Y (2014) A competitive swarm optimizer for large scale optimization. IEEE Transactions on Cybernetics 45(2):191\u2013204","journal-title":"IEEE Transactions on Cybernetics"},{"key":"68_CR10","doi-asserted-by":"crossref","unstructured":"Talbi EG (2009) Metaheuristics: from design to implementation, volume 74. John Wiley & Sons","DOI":"10.1002\/9780470496916"},{"issue":"2","key":"68_CR11","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/BF01876141","volume":"1","author":"F Archetti","year":"1984","unstructured":"Archetti F, Schoen F (1984) A survey on the global optimization problem: general theory and computational approaches. Ann Oper Res 1(2):87\u2013110","journal-title":"Ann Oper Res"},{"key":"68_CR12","unstructured":"Fister\u00a0Jr I, Yang XS, Fister I, Brest J, Fister D (2013) A brief review of nature-inspired algorithms for optimization. arXiv preprint arXiv:1307.4186"},{"key":"68_CR13","unstructured":"Talbi EG (2020) Machine learning into metaheuristics: a survey and taxonomy of data-driven metaheuristics"},{"key":"68_CR14","unstructured":"Dechter R. (2003) Constraint processing. Morgan Kaufmann"},{"key":"68_CR15","doi-asserted-by":"crossref","unstructured":"Fomin FV, Kratsch D (2010)\u00a0Exact exponential algorithms. Springer Science & Business Media","DOI":"10.1007\/978-3-642-16533-7"},{"key":"68_CR16","doi-asserted-by":"crossref","unstructured":"Applegate D, Bixby R, Cook W, Chv\u00e1tal V (1998) On the solution of traveling salesman problems. CRPC-TR98744","DOI":"10.4171\/dms\/1-3\/62"},{"key":"68_CR17","unstructured":"Cheeseman PC, Kanefsky B, Taylor WM (1991) Where the really hard problems are. In IJCAI\u00a0(91)331\u2013337"},{"issue":"1","key":"68_CR18","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10462-012-9328-0","volume":"42","author":"D Karaboga","year":"2014","unstructured":"Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (abc) algorithm and applications. Artif Intell Rev 42(1):21\u201357","journal-title":"Artif Intell Rev"},{"key":"68_CR19","doi-asserted-by":"crossref","unstructured":"Zhang Y, Wang S, Ji G (2015) A comprehensive survey on particle swarm optimization algorithm and its applications. Math Probl Eng","DOI":"10.1155\/2015\/931256"},{"key":"68_CR20","doi-asserted-by":"crossref","unstructured":"Yang XS (2010) Engineering optimization: an introduction with metaheuristic applications. John Wiley & Sons","DOI":"10.1002\/9780470640425"},{"key":"68_CR21","doi-asserted-by":"crossref","unstructured":"Xu L, Hutter F, Hoos H, Leyton-Brown K (2012) Evaluating component solver contributions to portfolio-based algorithm selectors. In International Conference on Theory and Applications of Satisfiability Testing. Springer,\u00a0pp. 228\u2013241","DOI":"10.1007\/978-3-642-31612-8_18"},{"issue":"1","key":"68_CR22","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s00500-003-0328-5","volume":"9","author":"Y Jin","year":"2005","unstructured":"Jin Y (2005) A comprehensive survey of fitness approximation in evolutionary computation. Soft Comput 9(1):3\u201312","journal-title":"Soft Comput"},{"key":"68_CR23","doi-asserted-by":"crossref","unstructured":"Zanakis SH, Evans JR (1981) Heuristic \u201coptimization\u201d: Why, when, and how to use it. Interfaces\u00a011(5):84\u201391","DOI":"10.1287\/inte.11.5.84"},{"key":"68_CR24","doi-asserted-by":"crossref","unstructured":"Crainic TG, Toulouse M (2003) Parallel strategies for meta-heuristics. In Handbook of metaheuristics. Springer,\u00a0pp. 475\u2013513","DOI":"10.1007\/0-306-48056-5_17"},{"key":"68_CR25","doi-asserted-by":"crossref","unstructured":"Szu HH, Hartley RL (1987) Nonconvex optimization by fast simulated annealing. Proceedings of the IEEE\u00a075(11):1538\u20131540","DOI":"10.1109\/PROC.1987.13916"},{"key":"68_CR26","doi-asserted-by":"crossref","unstructured":"Tsallis C, Stariolo DA (1996) Generalized simulated annealing. Physica A\u00a0233(1-2):395\u2013406","DOI":"10.1016\/S0378-4371(96)00271-3"},{"key":"68_CR27","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1103\/PhysRevLett.50.1411","volume":"50","author":"M Creutz","year":"1983","unstructured":"Creutz M (1983) Microcanonical monte carlo simulation. Phys Rev Lett 50:1411\u20131414","journal-title":"Phys Rev Lett"},{"issue":"1","key":"68_CR28","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/0021-9991(90)90201-B","volume":"90","author":"G Dueck","year":"1990","unstructured":"Dueck G, Scheuer T (1990) Threshold accepting: a general purpose optimization algorithm appearing superior to simulated annealing. J Comput Phys 90(1):161\u2013175","journal-title":"J Comput Phys"},{"key":"68_CR29","doi-asserted-by":"crossref","unstructured":"El\u00a0Yafrani M, Ahiod B (2016) Population-based vs. single-solution heuristics for the travelling thief problem. In Proceedings of the Genetic and Evolutionary Computation Conference 2016. ACM,\u00a0pp. 317\u2013324","DOI":"10.1145\/2908812.2908847"},{"key":"68_CR30","doi-asserted-by":"crossref","unstructured":"Van\u00a0Laarhoven PJ, Aarts EH, Lenstra JK (1992) Job shop scheduling by simulated annealing. Oper Res 40(1):113\u2013125","DOI":"10.1287\/opre.40.1.113"},{"key":"68_CR31","doi-asserted-by":"crossref","unstructured":"Delahaye D, Chaimatanan S, Mongeau M (2019) Simulated annealing: From basics to applications. In Handbook of Metaheuristics. Springer,\u00a0pp. 1\u201335","DOI":"10.1007\/978-3-319-91086-4_1"},{"issue":"1","key":"68_CR32","first-page":"1","volume":"5","author":"Z Beheshti","year":"2013","unstructured":"Beheshti Z, Shamsuddin SM (2013) A review of population-based meta-heuristic algorithms. Int J Adv Soft Comput Appl 5(1):1\u201335","journal-title":"Int J Adv Soft Comput Appl"},{"issue":"4","key":"68_CR33","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1080\/0952813X.2013.782347","volume":"25","author":"A Gogna","year":"2013","unstructured":"Gogna A, Tayal A (2013) Metaheuristics: review and application. J Exp Theor Artif Intell 25(4):503\u2013526","journal-title":"J Exp Theor Artif Intell"},{"key":"68_CR34","doi-asserted-by":"crossref","unstructured":"Stuckman B, Evans G, Mollaghasemi M (1991) Comparison of global search methods for design optimization using simulation. In 1991 Winter Simulation Conference Proceedings. IEEE, pp. 937\u2013944","DOI":"10.1109\/WSC.1991.185708"},{"issue":"4","key":"68_CR35","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/BF01889682","volume":"2","author":"AC Atkinson","year":"1992","unstructured":"Atkinson AC (1992) A segmented algorithm for simulated annealing. Stat Comput 2(4):221\u2013230","journal-title":"Stat Comput"},{"key":"68_CR36","doi-asserted-by":"crossref","unstructured":"Stokes Z, Mandal A, Wong WK (2020) Using differential evolution to design optimal experiments. Chemom Intell Lab Syst\u00a0199:103955","DOI":"10.1016\/j.chemolab.2020.103955"},{"key":"68_CR37","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-R\u00f3denas R, Garc\u00eda-Garc\u00eda JC, L\u00f3pez-Fidalgo J, Mart\u00edn-Baos JA, Wong WK (2020) A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs. Comput Stat Data Anal\u00a0144:106844","DOI":"10.1016\/j.csda.2019.106844"},{"key":"68_CR38","doi-asserted-by":"crossref","unstructured":"Shi Y, Zhang Z, Wong WK (2019) Particle swarm based algorithms for finding locally and bayesian d-optimal designs. Journal of Statistical Distributions and Applications\u00a06(1):3","DOI":"10.1186\/s40488-019-0092-4"},{"key":"68_CR39","unstructured":"Mahmudy WF (2016) Improved simulated annealing for optimization of vehicle routing problem with time windows (vrptw). Kursor 7(3)"},{"key":"68_CR40","unstructured":"Kose A, Sonmez BA, Balaban M (2017) Simulated annealing algorithm for graph coloring. arXiv preprint arXiv:1712.00709"},{"issue":"4","key":"68_CR41","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1023\/A:1009632422509","volume":"5","author":"T Emden-Weinert","year":"1999","unstructured":"Emden-Weinert T, Proksch M (1999) Best practice simulated annealing for the airline crew scheduling problem. J Heuristics 5(4):419\u2013436","journal-title":"J Heuristics"},{"key":"68_CR42","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.cie.2014.01.002","volume":"70","author":"R Hanafi","year":"2014","unstructured":"Hanafi R, Kozan E (2014) A hybrid constructive heuristic and simulated annealing for railway crew scheduling. Comput Ind Eng 70:11\u201319","journal-title":"Comput Ind Eng"},{"issue":"3","key":"68_CR43","doi-asserted-by":"publisher","first-page":"313","DOI":"10.3390\/mca18030313","volume":"18","author":"H Bayram","year":"2013","unstructured":"Bayram H, \u015eahin R (2013) A new simulated annealing approach for travelling salesman problem. Mathematical and Computational Applications 18(3):313\u2013322","journal-title":"Mathematical and Computational Applications"},{"issue":"2","key":"68_CR44","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1145\/264029.264043","volume":"23","author":"P Siarry","year":"1997","unstructured":"Siarry P, Berthiau G, Durdin F, Haussy J (1997) Enhanced simulated annealing for globally minimizing functions of many-continuous variables. ACM Trans Math Softw (TOMS) 23(2):209\u2013228","journal-title":"ACM Trans Math Softw (TOMS)"},{"key":"68_CR45","doi-asserted-by":"crossref","unstructured":"Connolly DT (1990) An improved annealing scheme for the qap. Eur J Oper Res\u00a046(1):93\u2013100","DOI":"10.1016\/0377-2217(90)90301-Q"},{"issue":"4","key":"68_CR46","doi-asserted-by":"publisher","first-page":"497","DOI":"10.15388\/Informatica.2003.037","volume":"14","author":"A Misevi\u010dius","year":"2003","unstructured":"Misevi\u010dius A (2003) A modified simulated annealing algorithm for the quadratic assignment problem. Informatica 14(4):497\u2013514","journal-title":"Informatica"},{"key":"68_CR47","doi-asserted-by":"crossref","unstructured":"Freitas AA (2003) A survey of evolutionary algorithms for data mining and knowledge discovery. In Advances in Evolutionary Computing. Springer,\u00a0pp 819\u2013845","DOI":"10.1007\/978-3-642-18965-4_33"},{"issue":"4\u20135","key":"68_CR48","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/BF02823145","volume":"24","author":"K Deb","year":"1999","unstructured":"Deb K (1999) An introduction to genetic algorithms. Sadhana 24(4\u20135):293\u2013315","journal-title":"Sadhana"},{"key":"68_CR49","unstructured":"Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning, addisson-wesley. Reading, MA"},{"issue":"5","key":"68_CR50","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1007\/s00158-005-0527-z","volume":"30","author":"CC Coello","year":"2005","unstructured":"Coello CC, Pulido GT (2005) Multiobjective structural optimization using a microgenetic algorithm. Struct Multidiscip Optim 30(5):388\u2013403","journal-title":"Struct Multidiscip Optim"},{"key":"68_CR51","doi-asserted-by":"crossref","unstructured":"Krishnakumar K (1990) Micro-genetic algorithms for stationary and non-stationary function optimization. In Intelligent Control and Adaptive Systems. International Society for Optics and Photonics\u00a01196:289\u2013297","DOI":"10.1117\/12.969927"},{"key":"68_CR52","unstructured":"Syswerda G (1989) Uniform crossover in genetic algorithms. In Proceedings of the third international conference on Genetic algorithms.\u00a0Morgan Kaufmann Publishers, pp 2\u20139"},{"key":"68_CR53","doi-asserted-by":"crossref","unstructured":"Ono I, Kita H, Kobayashi S (2003) A real-coded genetic algorithm using the unimodal normal distribution crossover. In Advances in Evolutionary Computing. Springer,\u00a0pp 213\u2013237","DOI":"10.1007\/978-3-642-18965-4_8"},{"key":"68_CR54","unstructured":"Ono I, Kita H, Kobayashi S (1999) A robust real-coded genetic algorithm using unimodal normal distribution crossover augmented by uniform crossover: effects of self-adaptation of crossover probabilities. In Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation-Volume 1. Morgan Kaufmann Publishers Inc., pp 496\u2013503"},{"issue":"2","key":"68_CR55","first-page":"115","volume":"9","author":"K Deb","year":"1995","unstructured":"Deb K, Agrawal RB (1995) Simulated binary crossover for continuous search space. Complex Systems 9(2):115\u2013148","journal-title":"Complex Systems"},{"key":"68_CR56","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez AM, Lozano M, Villar P, Herrera F (2009) Hybrid crossover operators with multiple descendents for real-coded genetic algorithms: Combining neighborhood-based crossover operators. Int J Intell Syst 24(5):540\u2013567","DOI":"10.1002\/int.20348"},{"key":"68_CR57","doi-asserted-by":"crossref","unstructured":"Eshelman LJ, Schaffer JD (1993) Real-coded genetic algorithms and interval-schemata. In Foundations of genetic algorithms.\u00a0Elsevier,\u00a0vol 2, pp 187\u2013202","DOI":"10.1016\/B978-0-08-094832-4.50018-0"},{"key":"68_CR58","doi-asserted-by":"crossref","unstructured":"Takahashi M, Kita H (2001) A crossover operator using independent component analysis for real-coded genetic algorithms. In Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546), volume\u00a01, pages 643\u2013649","DOI":"10.1109\/CEC.2001.934452"},{"key":"68_CR59","doi-asserted-by":"crossref","unstructured":"Munteanu C, Lazarescu V (1999) Improving mutation capabilities in a real-coded genetic algorithm. In Workshops on Applications of Evolutionary Computation. Springer,\u00a0pp 138\u2013149","DOI":"10.1007\/10704703_11"},{"key":"68_CR60","doi-asserted-by":"crossref","unstructured":"Korejo I, Yang S, Li C (2010) A directed mutation operator for real coded genetic algorithms. In European Conference on the Applications of Evolutionary Computation. Springer, pp 491\u2013500","DOI":"10.1007\/978-3-642-12239-2_51"},{"issue":"3","key":"68_CR61","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1162\/evco.1994.2.3.221","volume":"2","author":"N Srinivas","year":"1994","unstructured":"Srinivas N, Deb K (1994) Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evol Comput 2(3):221\u2013248","journal-title":"Evol Comput"},{"key":"68_CR62","unstructured":"Rechenberg I (1965) Cybernetic solution path of an experimental problem. In Royal Aircraft Establishment Library Translation"},{"key":"68_CR63","volume-title":"Numerical Optimization of Computer Models","author":"HP Schwefel","year":"1981","unstructured":"Schwefel HP (1981) Numerical Optimization of Computer Models. John Wiley & Sons Inc, New York, NY, USA"},{"key":"68_CR64","unstructured":"Fogel DB (1991)\u00a0System Identification Through Simulated Evolution: A Machine Learning Approach to Modeling. Ginn Press"},{"key":"68_CR65","unstructured":"Fogel DB (1992) Evolving artificial intelligence. Doctoral Dissertation"},{"key":"68_CR66","doi-asserted-by":"crossref","unstructured":"Fogel DB (1993) Applying evolutionary programming to selected traveling salesman problems. Cybern Syst\u00a024(1):27\u201336","DOI":"10.1080\/01969729308961697"},{"key":"68_CR67","doi-asserted-by":"crossref","unstructured":"Fogel DB (2006)\u00a0Evolutionary computation: toward a new philosophy of machine intelligence.\u00a0John Wiley & Sons, vol 1","DOI":"10.1002\/0471749214"},{"key":"68_CR68","first-page":"451","volume":"3","author":"X Yao","year":"1996","unstructured":"Yao X, Liu Y (1996) Fast evolutionary programming. Evolutionary Programming 3:451\u2013460","journal-title":"Evolutionary Programming"},{"issue":"2","key":"68_CR69","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3(2):82\u2013102","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"68_CR70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TEVC.2003.816583","volume":"8","author":"CY Lee","year":"2004","unstructured":"Lee CY, Yao X (2004) Evolutionary programming using mutations based on the l\u00e9vy probability distribution. IEEE Trans Evol Comput 8(1):1\u201313","journal-title":"IEEE Trans Evol Comput"},{"key":"68_CR71","doi-asserted-by":"crossref","unstructured":"Fogel DB (1997) The advantages of evolutionary computation. In BCEC\u00a0p 1\u201311","DOI":"10.1201\/9781420050387"},{"key":"68_CR72","doi-asserted-by":"crossref","unstructured":"Wieland AP (1991) Evolving controls for unstable systems. In Connectionist Models.\u00a0Elsevier, pp 91\u2013102","DOI":"10.1016\/B978-1-4832-1448-1.50015-9"},{"key":"68_CR73","first-page":"20","volume":"1","author":"HP Schwefel","year":"2000","unstructured":"Schwefel HP (2000) Advantages (and disadvantages) of evolutionary computation over other approaches. Evol Comput 1:20\u201322","journal-title":"Evol Comput"},{"issue":"2","key":"68_CR74","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1109\/4235.850651","volume":"4","author":"C Dimopoulos","year":"2000","unstructured":"Dimopoulos C, Zalzala AMS (2000) Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons. IEEE Trans Evol Comput 4(2):93\u2013113","journal-title":"IEEE Trans Evol Comput"},{"key":"68_CR75","doi-asserted-by":"crossref","unstructured":"Simpson AR, Dandy GC, Murphy LJ (1994) Genetic algorithms compared to other techniques for pipe optimization. J Water Resour Plan Manag\u00a0120(4):423\u2013443","DOI":"10.1061\/(ASCE)0733-9496(1994)120:4(423)"},{"key":"68_CR76","doi-asserted-by":"crossref","unstructured":"Chu PC, Beasley JE (1997) A genetic algorithm for the generalised assignment problem. Comput Oper Res\u00a024(1):17\u201323","DOI":"10.1016\/S0305-0548(96)00032-9"},{"key":"68_CR77","doi-asserted-by":"crossref","unstructured":"Alba E, Troya JM et\u00a0al (1999) A survey of parallel distributed genetic algorithms. Complexity\u00a04(4):31\u201352","DOI":"10.1002\/(SICI)1099-0526(199903\/04)4:4<31::AID-CPLX5>3.0.CO;2-4"},{"key":"68_CR78","doi-asserted-by":"crossref","unstructured":"Reddy GT, Reddy MP, Lakshmanna K, Rajput DS, Kaluri R, Srivastava G (2020) Hybrid genetic algorithm and a fuzzy logic classifier for heart disease diagnosis. Evol Intell\u00a013(2):185\u2013196","DOI":"10.1007\/s12065-019-00327-1"},{"key":"68_CR79","doi-asserted-by":"publisher","first-page":"114169","DOI":"10.1016\/j.apenergy.2019.114169","volume":"260","author":"Y Zhou","year":"2020","unstructured":"Zhou Y, Wang Y, Wang K, Kang L, Peng F, Wang L, Pang J (2020) Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors. Appl Energy 260:114169","journal-title":"Appl Energy"},{"key":"68_CR80","doi-asserted-by":"crossref","unstructured":"Back T (1996) Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms. Oxford University Press","DOI":"10.1093\/oso\/9780195099713.001.0001"},{"key":"68_CR81","doi-asserted-by":"crossref","unstructured":"Moslemipour G, Lee TS, Rilling D (2012) A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. Int J Adv Manuf Technol\u00a060(1-4):11\u201327","DOI":"10.1007\/s00170-011-3614-x"},{"issue":"5","key":"68_CR82","doi-asserted-by":"publisher","first-page":"1165","DOI":"10.1109\/72.623217","volume":"8","author":"Y Leung","year":"1997","unstructured":"Leung Y, Gao Y, Zong-Ben X (1997) Degree of population diversity-a perspective on premature convergence in genetic algorithms and its markov chain analysis. IEEE Trans Neural Netw 8(5):1165\u20131176","journal-title":"IEEE Trans Neural Netw"},{"issue":"3\u20134","key":"68_CR83","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/S0965-9978(03)00113-3","volume":"35","author":"O Hrstka","year":"2004","unstructured":"Hrstka O, Ku\u010derov\u00e1 A (2004) Improvements of real coded genetic algorithms based on differential operators preventing premature convergence. Adv Eng Softw 35(3\u20134):237\u2013246","journal-title":"Adv Eng Softw"},{"key":"68_CR84","doi-asserted-by":"crossref","unstructured":"Fogel DB (1995) A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems. Simulation\u00a064(6):397\u2013404","DOI":"10.1177\/003754979506400605"},{"key":"68_CR85","unstructured":"Swayamsiddha S, Thethi HP. Nonlinear system identification using evolutionary computing based training schemes. Int J Comput Appl\u00a0975:8887"},{"issue":"4","key":"68_CR86","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341\u2013359","journal-title":"J Glob Optim"},{"key":"68_CR87","unstructured":"Li J, Aickelin U (2003) A bayesian optimization algorithm for the nurse scheduling problem. In The 2003 Congress on Evolutionary Computation, 2003. CEC\u201903., vol 3, pp 2149\u20132156"},{"key":"68_CR88","doi-asserted-by":"crossref","unstructured":"Larranaga P, Kuijpers CMH, Murga RH, Inza I, Dizdarevic S (1999) Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artif Intell Rev\u00a013(2):129\u2013170","DOI":"10.1023\/A:1006529012972"},{"key":"68_CR89","doi-asserted-by":"crossref","unstructured":"Hussain A, Muhammad YS, Sajid MN, Hussain I, Shoukry AM, Gani S (2017) Genetic algorithm for traveling salesman problem with modified cycle crossover operator. Comput Intell Neurosci","DOI":"10.1155\/2017\/7430125"},{"key":"68_CR90","unstructured":"Davis L (1985) Job shop scheduling with genetic algorithms. In Proceedings of an international conference on genetic algorithms and their applications, vol 140"},{"key":"68_CR91","doi-asserted-by":"crossref","unstructured":"Chan H, Mazumder P, Shahookar K (1991) Macro-cell and module placement by genetic adaptive search with bitmap-represented chromosome. VLSI, 12(1)","DOI":"10.1016\/0167-9260(91)90042-J"},{"issue":"13","key":"68_CR92","doi-asserted-by":"publisher","first-page":"5917","DOI":"10.1016\/j.eswa.2014.03.034","volume":"41","author":"K Boudjelaba","year":"2014","unstructured":"Boudjelaba K, Ros F, Chikouche D (2014) An efficient hybrid genetic algorithm to design finite impulse response filters. Expert Systems with Applications 41(13):5917\u20135937","journal-title":"Expert Systems with Applications"},{"issue":"5","key":"68_CR93","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1007\/s00034-005-0721-7","volume":"25","author":"N Karaboga","year":"2006","unstructured":"Karaboga N, Cetinkaya B (2006) Design of digital fir filters using differential evolution algorithm. Circuits Systems Signal Process 25(5):649\u2013660","journal-title":"Circuits Systems Signal Process"},{"key":"68_CR94","first-page":"2005","volume":"1269\u20131276","author":"N Karaboga","year":"2005","unstructured":"Karaboga N (2005) Digital iir filter design using differential evolution algorithm. EURASIP Journal on Applied Signal Processing 1269\u20131276:2005","journal-title":"EURASIP Journal on Applied Signal Processing"},{"key":"68_CR95","doi-asserted-by":"crossref","unstructured":"Storn S (1996) Differential evolution design of an iir-filter. In Proceedings of IEEE international conference on evolutionary computation. IEEE,\u00a0pp 268\u2013273","DOI":"10.1109\/ICEC.1996.542373"},{"key":"68_CR96","unstructured":"Dasgupta D, Michalewicz Z (2013)\u00a0Evolutionary algorithms in engineering applications. Springer Science & Business Media"},{"issue":"5","key":"68_CR97","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1109\/41.538609","volume":"43","author":"KF Man","year":"1996","unstructured":"Man KF, Tang KS, Kwong Sam (1996) Genetic algorithms: concepts and applications [in engineering design]. IEEE Trans Ind Electron 43(5):519\u2013534","journal-title":"IEEE Trans Ind Electron"},{"key":"68_CR98","doi-asserted-by":"crossref","unstructured":"Bhoskar MT, Kulkarni OK, Kulkarni NK, Patekar SL, Kakandikar GM, Nandedkar VM (2015) Genetic algorithm and its applications to mechanical engineering: A review. Materials Today: Proceedings\u00a02(4-5):2624\u20132630","DOI":"10.1016\/j.matpr.2015.07.219"},{"issue":"11","key":"68_CR99","doi-asserted-by":"publisher","first-page":"1327","DOI":"10.1016\/S1474-6670(17)43026-6","volume":"30","author":"T Hatanaka","year":"1997","unstructured":"Hatanaka T, Uosaki K, Yamada Y (1997) Evolutionary approach to system identification. IFAC Proceedings Volumes 30(11):1327\u20131332","journal-title":"IFAC Proceedings Volumes"},{"key":"68_CR100","unstructured":"Fahmi M, Samad A (2014) Evolutionary computation in system identification: Review and recommendations. Int J Autom Control\u00a0pp 208\u2013216"},{"key":"68_CR101","doi-asserted-by":"crossref","unstructured":"Lewin DR (2005) Evolutionary algorithms in control system engineering. IFAC Proceedings Volumes\u00a038(1):45\u201350","DOI":"10.3182\/20050703-6-CZ-1902.00868"},{"key":"68_CR102","doi-asserted-by":"crossref","unstructured":"Fleming PJ, Purshouse RC (2002) Evolutionary algorithms in control systems engineering: a survey. Control Eng Pract 10(11):1223\u20131241","DOI":"10.1016\/S0967-0661(02)00081-3"},{"key":"68_CR103","doi-asserted-by":"crossref","unstructured":"Alcal\u00e1-Fdez J, Sanchez L, Garcia S, del Jesus MJ, Ventura S, Garrell JM, Otero J, Romero C, Bacardit J, Rivas VM et\u00a0al (2009) Keel: a software tool to assess evolutionary algorithms for data mining problems. Soft Comput\u00a013(3):307\u2013318","DOI":"10.1007\/s00500-008-0323-y"},{"key":"68_CR104","unstructured":"Bounsaythip C, Alander JT (1997) Genetic algorithms in image processing-a review. In Proceedings of the Third Nordic Workshop on Genetic Algorithms and their Applications (3NWGA)\u00a0pp 173\u2013192"},{"key":"68_CR105","unstructured":"Paulinas M, U\u0161inskas A (2007) A survey of genetic algorithms applications for image enhancement and segmentation. Inf Tech Control 36(3)"},{"key":"68_CR106","doi-asserted-by":"crossref","unstructured":"Omran MG, Engelbrecht AP, Salman A (2005) Differential evolution methods for unsupervised image classification. In 2005 IEEE Congress on Evolutionary Computation. IEEE\u00a02:966\u2013973","DOI":"10.1109\/CEC.2005.1554795"},{"key":"68_CR107","doi-asserted-by":"crossref","unstructured":"Bonabeau E, Marco DD, Dorigo M, Theraulaz G et\u00a0al (1999)\u00a0Swarm intelligence: from natural to artificial systems.\u00a0Oxford University Press, vol 1","DOI":"10.1093\/oso\/9780195131581.001.0001"},{"key":"68_CR108","doi-asserted-by":"crossref","unstructured":"Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In Micro Machine and Human Science, 1995. MHS\u201995., Proceedings of the Sixth International Symposium on. IEEE\u00a0pp 39\u201343","DOI":"10.1109\/MHS.1995.494215"},{"key":"68_CR109","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1999) Empirical study of particle swarm optimization. In Evolutionary computation, 1999. CEC 99. Proceedings of the 1999 congress on. IEEE\u00a03:1945\u20131950","DOI":"10.1109\/CEC.1999.785511"},{"key":"68_CR110","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart R (1998) A modified particle swarm optimizer. In Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on. IEEE\u00a0pp 69\u201373","DOI":"10.1109\/ICEC.1998.699146"},{"key":"68_CR111","doi-asserted-by":"crossref","unstructured":"Zheng YL, Ma LH, Zhang LY, Qian JX (2003) Empirical study of particle swarm optimizer with an increasing inertia weight. In Evolutionary Computation, 2003. CEC\u201903. The 2003 Congress on. IEEE\u00a01:221\u2013226","DOI":"10.1109\/CEC.2003.1299578"},{"issue":"1","key":"68_CR112","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/4235.985692","volume":"6","author":"M Clerc","year":"2002","unstructured":"Clerc M, Kennedy J (2002) The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58\u201373","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"68_CR113","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1109\/TEVC.2004.826074","volume":"8","author":"R Mendes","year":"2004","unstructured":"Mendes R, Kennedy J, Neves J (2004) The fully informed particle swarm: simpler, maybe better. IEEE Trans Evol Comput 8(3):204\u2013210","journal-title":"IEEE Trans Evol Comput"},{"key":"68_CR114","doi-asserted-by":"crossref","unstructured":"Ratnaweera A, Halgamuge SK, Watson HC (2004) Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans Evol Comput\u00a08(3):240\u2013255","DOI":"10.1109\/TEVC.2004.826071"},{"key":"68_CR115","doi-asserted-by":"crossref","unstructured":"Mohapatra P, Das KN, Roy S (2017) A modified competitive swarm optimizer for large scale optimization problems. Appl Soft Comput\u00a059:340\u2013362","DOI":"10.1016\/j.asoc.2017.05.060"},{"key":"68_CR116","doi-asserted-by":"crossref","unstructured":"Mohapatra P, Das KN, Roy S (2019) Inherited competitive swarm optimizer for large-scale optimization problems. In Harmony Search and Nature Inspired Optimization Algorithms. Springer,\u00a0pp 85\u201395","DOI":"10.1007\/978-981-13-0761-4_9"},{"key":"68_CR117","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.neucom.2012.09.039","volume":"125","author":"H Duan","year":"2014","unstructured":"Duan H, Huang L (2014) Imperialist competitive algorithm optimized artificial neural networks for ucav global path planning. Neurocomputing 125:166\u2013171","journal-title":"Neurocomputing"},{"key":"68_CR118","volume-title":"Swarm intelligence: concepts, models and applications","author":"H Ahmed","year":"2012","unstructured":"Ahmed H, Glasgow J (2012) Swarm intelligence: concepts, models and applications. Queens University Technical Report, School Of Computing"},{"key":"68_CR119","doi-asserted-by":"crossref","unstructured":"Olariu S, Zomaya AY (2005)\u00a0Handbook of bioinspired algorithms and applications. Chapman and Hall\/CRC","DOI":"10.1201\/9781420035063"},{"issue":"1","key":"68_CR120","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.aei.2005.01.004","volume":"19","author":"E Elbeltagi","year":"2005","unstructured":"Elbeltagi E, Hegazy T, Grierson D (2005) Comparison among five evolutionary-based optimization algorithms. Adv Eng Inform 19(1):43\u201353","journal-title":"Adv Eng Inform"},{"key":"68_CR121","doi-asserted-by":"crossref","unstructured":"Hassan R, Cohanim B, De\u00a0Weck O, Venter G (2005) A comparison of particle swarm optimization and the genetic algorithm. In 46th AIAA\/ASME\/ASCE\/AHS\/ASC structures, structural dynamics and materials conference\u00a0p\u00a01897","DOI":"10.2514\/6.2005-1897"},{"key":"68_CR122","unstructured":"Rahmat-Samii Y (2003) Genetic algorithm (ga) and particle swarm optimization (pso) in engineering electromagnetics. In 17th International Conference on Applied Electromagnetics and Communications. ICECom IEEE,\u00a0pp 1\u20135"},{"key":"68_CR123","volume-title":"Antenna Engineering Using Physical Optics: Practical CAD Techniques and Software","author":"L Diaz","year":"1996","unstructured":"Diaz L, Milligan TA (1996) Antenna Engineering Using Physical Optics: Practical CAD Techniques and Software, 1st edn. Artech House Inc, Norwood, MA, USA","edition":"1"},{"key":"68_CR124","unstructured":"Afandie WN, Rahman TK, Zakaria Z (2016) Comparative analysis of bacterial foraging optimization algorithm and evolutionary programming for load shedding in power system. Int J Simul Syst Sci Technol\u00a017(41)"},{"key":"68_CR125","doi-asserted-by":"crossref","unstructured":"Alsariera YA, Alamri HS, Nasser AM, Majid MA, Zamli KZ (2014) Comparative performance analysis of bat algorithm and bacterial foraging optimization algorithm using standard benchmark functions. In 2014 8th. Malaysian Software Engineering Conference (MySEC). IEEE,\u00a0pp 295\u2013300","DOI":"10.1109\/MySec.2014.6986032"},{"key":"68_CR126","doi-asserted-by":"crossref","unstructured":"Kamalanand K, Jawahar PM (2016) Comparison of particle swarm and bacterial foraging optimization algorithms for therapy planning in hiv\/aids patients. Int J Biomath\u00a09(02):1650024","DOI":"10.1142\/S1793524516500248"},{"key":"68_CR127","doi-asserted-by":"crossref","unstructured":"Ji X, Gao Q, Yin F, Guo H (2016) An efficient imperialist competitive algorithm for solving the qfd decision problem. Math Probl Eng","DOI":"10.1155\/2016\/2601561"},{"issue":"2","key":"68_CR128","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/TEVC.2019.2921598","volume":"24","author":"C Huang","year":"2019","unstructured":"Huang C, Li Y, Yao X (2019) A survey of automatic parameter tuning methods for metaheuristics. IEEE Trans Evol Comput 24(2):201\u2013216","journal-title":"IEEE Trans Evol Comput"},{"key":"68_CR129","unstructured":"Birattari M, St\u00fctzle T, Paquete L, Varrentrapp K et\u00a0al (2002) A racing algorithm for configuring metaheuristics. In Gecco, vol 2"},{"key":"68_CR130","doi-asserted-by":"crossref","unstructured":"Yuan B, Gallagher M (2004) Statistical racing techniques for improved empirical evaluation of evolutionary algorithms. In International Conference on Parallel Problem Solving from Nature. Springer,\u00a0pp 172\u2013181","DOI":"10.1007\/978-3-540-30217-9_18"},{"key":"68_CR131","unstructured":"Chen L, Xu X, Chen YX (2004) An adaptive ant colony clustering algorithm. In Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No. 04EX826), vol 3, pp 1387\u20131392"},{"key":"68_CR132","doi-asserted-by":"crossref","unstructured":"Chen H, Zhu Y, Hu K (2011) Adaptive bacterial foraging optimization. In Abstract and Applied Analysis. Hindawi,\u00a0vol\u00a02011","DOI":"10.1155\/2011\/108269"},{"issue":"4","key":"68_CR133","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1109\/TEVC.2009.2021982","volume":"13","author":"S Dasgupta","year":"2009","unstructured":"Dasgupta S, Das S, Abraham A, Biswas A (2009) Adaptive computational chemotaxis in bacterial foraging optimization: an analysis. IEEE Trans Evol Comput 13(4):919\u2013941","journal-title":"IEEE Trans Evol Comput"},{"key":"68_CR134","unstructured":"Shi Y, Eberhart RC (2001) Fuzzy adaptive particle swarm optimization. In Proceedings of the 2001 congress on evolutionary computation (IEEE Cat. No. 01TH8546), vol 1, pp 101\u2013106"},{"issue":"2","key":"68_CR135","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1162\/106365601750190361","volume":"9","author":"T B\u00e4ck","year":"2001","unstructured":"B\u00e4ck T (2001) Introduction to the special issue: Self-adaptation. Evol Comput 9(2):3\u20134","journal-title":"Evol Comput"},{"key":"68_CR136","unstructured":"Clerc M (2006) Stagnation analysis in particle swarm optimisation or what happens when nothing happens. Tech Rep"},{"key":"68_CR137","doi-asserted-by":"crossref","unstructured":"Bouhouch A, Loqman C, Bennis H, El\u00a0Qadi A (2019) A comparative study of chn-mnc, ga and pso for solving constraints satisfaction problems. In Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019. European Alliance for Innovation (EAI)","DOI":"10.4108\/eai.24-4-2019.2284084"},{"key":"68_CR138","doi-asserted-by":"crossref","unstructured":"Abdi Y, Lak M, Seyfari Y (2017) Gica: Imperialist competitive algorithm with globalization mechanism for optimization problems. Turk J Electr Eng Comput Sci\u00a025(1):209\u2013221","DOI":"10.3906\/elk-1507-226"},{"issue":"9\u201312","key":"68_CR139","doi-asserted-by":"publisher","first-page":"2207","DOI":"10.1007\/s00170-012-4641-y","volume":"67","author":"W Zhou","year":"2013","unstructured":"Zhou W, Yan J, Li Y, Xia C, Zheng J (2013) Imperialist competitive algorithm for assembly sequence planning. Int J Adv Manuf Technol 67(9\u201312):2207\u20132216","journal-title":"Int J Adv Manuf Technol"},{"issue":"2","key":"68_CR140","first-page":"2231","volume":"2","author":"R Vijay","year":"2012","unstructured":"Vijay R (2012) Intelligent bacterial foraging optimization technique to economic load dispatch problem. International Journal of Soft Computing and Engineering (IJSCE) 2(2):2231\u20132307","journal-title":"International Journal of Soft Computing and Engineering (IJSCE)"},{"key":"68_CR141","doi-asserted-by":"crossref","unstructured":"Sharvani GS, Ananth AG, Rangaswamy TM (2012) Analysis of different pheromone decay techniques for aco based routing in ad hoc wireless networks. Int J Comput Appl\u00a056(2)","DOI":"10.5120\/8866-2833"},{"key":"68_CR142","unstructured":"Jagadeesh S, Sugumar R (2017) A comparative study on artificial bee colony with modified abc algorithm. European Journal of Applied Sciences\u00a09(5):243\u2013248"},{"issue":"1","key":"68_CR143","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/TNET.2010.2055886","volume":"19","author":"Z Zhou","year":"2010","unstructured":"Zhou Z, Peng Z, Cui JH, Shi Z (2010) Efficient multipath communication for time-critical applications in underwater acoustic sensor networks. IEEE\/ACM Trans Networking 19(1):28\u201341","journal-title":"IEEE\/ACM Trans Networking"},{"issue":"12","key":"68_CR144","first-page":"5","volume":"83","author":"NS Pal","year":"2013","unstructured":"Pal NS, Sharma S (2013) Robot path planning using swarm intelligence: A survey. Int J Comput Appl 83(12):5\u201312","journal-title":"Int J Comput Appl"},{"key":"68_CR145","doi-asserted-by":"crossref","unstructured":"Fornarelli G (2012)\u00a0Swarm intelligence for electric and electronic engineering. IGI Global","DOI":"10.4018\/978-1-4666-2666-9"},{"key":"68_CR146","unstructured":"Ming L, Hai H, Aimin Z, Yingde S, Zhao L, Xingguo Z (2012) Modeling of mechanical properties of as-cast mg-li-al alloys based on pso-bp algorithm. China Foundry 9(2)"},{"key":"68_CR147","doi-asserted-by":"crossref","unstructured":"Mohan SC, Maiti DK, Maity D (2013) Structural damage assessment using frf employing particle swarm optimization. Appl Math Comput\u00a0219(20):10387\u201310400","DOI":"10.1016\/j.amc.2013.04.016"},{"key":"68_CR148","doi-asserted-by":"crossref","unstructured":"Lu P, Chen S, Zheng Y (2012) Artificial intelligence in civil engineering. Math Probl Eng","DOI":"10.1155\/2012\/145974"},{"key":"68_CR149","unstructured":"Omran MGH et\u00a0al (2004) Particle swarm optimization methods for pattern recognition and image processing. PhD thesis, Citeseer"},{"key":"68_CR150","volume-title":"An analysis of publications on particle swarm optimization applications","author":"R Poli","year":"2007","unstructured":"Poli R (2007) An analysis of publications on particle swarm optimization applications. Department of Computer Science, University of Essex, Essex, UK"},{"issue":"2","key":"68_CR151","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1109\/TCBB.2010.13","volume":"8","author":"S Saraswathi","year":"2011","unstructured":"Saraswathi S, Sundaram S, Sundararajan N, Zimmermann M, Nilsen-Hamilton M (2011) Icga-pso-elm approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented. IEEE\/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 8(2):452\u2013463","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics (TCBB)"},{"key":"68_CR152","unstructured":"Xu R, Cai X, Wunsch DC (2006) Gene expression data for dlbcl cancer survival prediction with a combination of machine learning technologies. In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference\u00a0pp 894\u2013897"},{"issue":"3","key":"68_CR153","first-page":"190","volume":"4","author":"N Mansour","year":"2012","unstructured":"Mansour N, Kanj F, Khachfe H (2012) Particle swarm optimization approach for protein structure prediction in the 3d hp model. Interdisciplinary Sciences: Computational Life Sciences 4(3):190\u2013200","journal-title":"Interdisciplinary Sciences: Computational Life Sciences"},{"issue":"9","key":"68_CR154","doi-asserted-by":"publisher","first-page":"2846","DOI":"10.1016\/j.asoc.2012.04.006","volume":"12","author":"M Karabulut","year":"2012","unstructured":"Karabulut M, Ibrikci T (2012) A bayesian scoring scheme based particle swarm optimization algorithm to identify transcription factor binding sites. Appl Soft Comput 12(9):2846\u20132855","journal-title":"Appl Soft Comput"},{"key":"68_CR155","doi-asserted-by":"crossref","unstructured":"Cedefto W, Agraflotis D (2005) Particle swarms for drug design. In 2005 IEEE Congress on Evolutionary Computation, vol 2, pp 1218\u20131225","DOI":"10.1109\/CEC.2005.1554829"},{"issue":"3","key":"68_CR156","doi-asserted-by":"publisher","first-page":"1013","DOI":"10.1007\/s11277-011-0496-z","volume":"68","author":"H Yongqiang","year":"2013","unstructured":"Yongqiang H, Wentao L, Xiaohui L (2013) Particle swarm optimization for antenna selection in mimo system. Wirel Pers Commun 68(3):1013\u20131029","journal-title":"Wirel Pers Commun"},{"issue":"3","key":"68_CR157","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1002\/mmce.20674","volume":"23","author":"CC Chiu","year":"2013","unstructured":"Chiu CC, Ho MH, Liao S (2013) Pso and apso for optimizing coverage in indoor uwb communication system. Int J RF Microwave Comput Aided Eng 23(3):300\u2013308","journal-title":"Int J RF Microwave Comput Aided Eng"},{"key":"68_CR158","doi-asserted-by":"crossref","unstructured":"Kim YG, Lee MJ (2014) Scheduling multi-channel and multi-timeslot in time constrained wireless sensor networks via simulated annealing and particle swarm optimization. IEEE Commun Mag 52(1):122\u2013129","DOI":"10.1109\/MCOM.2014.6710073"},{"key":"68_CR159","doi-asserted-by":"crossref","unstructured":"Das G, Pattnaik PK, Padhy SK (2014) Artificial neural network trained by particle swarm optimization for non-linear channel equalization. Expert Systems with Applications\u00a041(7):3491\u20133496","DOI":"10.1016\/j.eswa.2013.10.053"},{"key":"68_CR160","doi-asserted-by":"crossref","unstructured":"Goldansaz SM, Jolai F, Anaraki AHZ (2013) A hybrid imperialist competitive algorithm for minimizing makespan in a multi-processor open shop. Appl Math Model\u00a037(23):9603\u20139616","DOI":"10.1016\/j.apm.2013.05.002"},{"issue":"7","key":"68_CR161","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1016\/j.enconman.2010.01.014","volume":"51","author":"C Lucas","year":"2010","unstructured":"Lucas C, Nasiri-Gheidari Z, Tootoonchian F (2010) Application of an imperialist competitive algorithm to the design of a linear induction motor. Energy Convers Manag 51(7):1407\u20131411","journal-title":"Energy Convers Manag"},{"issue":"21\u201322","key":"68_CR162","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1016\/j.compstruc.2010.06.011","volume":"88","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88(21\u201322):1220\u20131229","journal-title":"Comput Struct"},{"issue":"13","key":"68_CR163","doi-asserted-by":"publisher","first-page":"1868","DOI":"10.1016\/j.patrec.2009.12.005","volume":"31","author":"H Duan","year":"2010","unstructured":"Duan H, Chunfang X, Liu S, Shao S (2010) Template matching using chaotic imperialist competitive algorithm. Pattern Recogn Lett 31(13):1868\u20131875","journal-title":"Pattern Recogn Lett"},{"key":"68_CR164","doi-asserted-by":"crossref","unstructured":"Nazari-Shirkouhi S, Eivazy H, Ghodsi R, Rezaie K, Atashpaz-Gargari E (2010) Solving the integrated product mix-outsourcing problem using the imperialist competitive algorithm. Expert Systems with Applications\u00a037(12):7615\u20137626","DOI":"10.1016\/j.eswa.2010.04.081"},{"issue":"1","key":"68_CR165","first-page":"11","volume":"10","author":"A Biabangard-Oskouyi","year":"2009","unstructured":"Biabangard-Oskouyi A, Atashpaz-Gargari E, Soltani N, Lucas C (2009) Application of imperialist competitive algorithm for materials property characterization from sharp indentation test. International Journal of Engineering Simulation 10(1):11\u201312","journal-title":"International Journal of Engineering Simulation"},{"key":"68_CR166","doi-asserted-by":"crossref","unstructured":"Rajabioun R, Hashemzadeh F, Atashpaz-Gargari E, Mesgari B, Rajaei Salmasi F (2008) Identification of a mimo evaporator and its decentralized pid controller tuning using colonial competitive algorithm. In be presented in IFAC World Congress","DOI":"10.1108\/17563780810893446"},{"key":"68_CR167","doi-asserted-by":"crossref","unstructured":"Forouharfard S, Zandieh M (2010) An imperialist competitive algorithm to schedule of receiving and shipping trucks in cross-docking systems. Int J Adv Manuf Technol\u00a051(9-12):1179\u20131193","DOI":"10.1007\/s00170-010-2676-5"},{"key":"68_CR168","doi-asserted-by":"crossref","unstructured":"Alba E, Chicano JF (2006) Evolutionary algorithms in telecommunications. In MELECON 2006-2006 IEEE Mediterranean Electrotechnical Conference, pp 795\u2013798","DOI":"10.1109\/MELCON.2006.1653218"},{"key":"68_CR169","doi-asserted-by":"crossref","unstructured":"Veeramachaneni K, Peram T, Mohan C, Osadciw LA (2003) Optimization using particle swarms with near neighbor interactions. In Genetic and Evolutionary Computation Conference. Springer,\u00a0pp 110\u2013121","DOI":"10.1007\/3-540-45105-6_10"},{"issue":"4","key":"68_CR170","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/MCI.2014.2350951","volume":"9","author":"S Chaimatanan","year":"2014","unstructured":"Chaimatanan S, Delahaye D, Mongeau M (2014) A hybrid metaheuristic optimization algorithm for strategic planning of 4d aircraft trajectories at the continental scale. IEEE Comput Intell Mag 9(4):46\u201361","journal-title":"IEEE Comput Intell Mag"},{"key":"68_CR171","doi-asserted-by":"crossref","unstructured":"Flores SD, Cegla BB, C\u00e1ceres DB (2003) Telecommunication network design with parallel multi-objective evolutionary algorithms. LANC\u00a03:3\u20135","DOI":"10.1145\/1035662.1035663"},{"key":"68_CR172","unstructured":"Fogel DB (2000)\u00a0Evolutionary computation: principles and practice for signal processing.\u00a0SPIE Press, vol 43"},{"key":"68_CR173","doi-asserted-by":"crossref","unstructured":"Fogel DB, Fogel LJ, Atmar JW (1991) Meta-evolutionary programming. In [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.\u00a0pp 540\u2013545","DOI":"10.1109\/ACSSC.1991.186507"},{"key":"68_CR174","doi-asserted-by":"crossref","unstructured":"Higashi N, Iba H (2003) Particle swarm optimization with gaussian mutation. In Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS\u201903 (Cat. No. 03EX706). IEEE,\u00a0pp 72\u201379","DOI":"10.1109\/SIS.2003.1202250"},{"issue":"1","key":"68_CR175","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1023\/A:1022995128597","volume":"17","author":"J Ilonen","year":"2003","unstructured":"Ilonen J, Kamarainen JK, Lampinen J (2003) Differential evolution training algorithm for feed-forward neural networks. Neural Process Lett 17(1):93\u2013105","journal-title":"Neural Process Lett"},{"key":"68_CR176","doi-asserted-by":"crossref","unstructured":"Miller JF, Job D, Vassilev VK (2000) Principles in the evolutionary design of digital circuits\u2013part i. Genet Program Evolvable Mach\u00a01(1-2):7\u201335","DOI":"10.1023\/A:1010016313373"},{"key":"68_CR177","unstructured":"Wong DF, Leong HW, Liu HW (2012)\u00a0Simulated annealing for VLSI design.\u00a0Springer Science & Business Media,\u00a0vol 42"},{"issue":"9","key":"68_CR178","doi-asserted-by":"publisher","first-page":"1423","DOI":"10.1109\/5.784219","volume":"87","author":"X Yao","year":"1999","unstructured":"Yao X (1999) Evolving artificial neural networks. Proceedings of the IEEE 87(9):1423\u20131447","journal-title":"Proceedings of the IEEE"},{"issue":"3","key":"68_CR179","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1109\/72.572107","volume":"8","author":"X Yao","year":"1997","unstructured":"Yao X, Liu Y (1997) A new evolutionary system for evolving artificial neural networks. IEEE Trans Neural Netw 8(3):694\u2013713","journal-title":"IEEE Trans Neural Netw"},{"key":"68_CR180","doi-asserted-by":"crossref","unstructured":"Zebulum RS, Pacheco MA, Be Vellasco MM (2018)\u00a0Evolutionary electronics: automatic design of electronic circuits and systems by genetic algorithms. CRC Press","DOI":"10.1201\/9781420041590"},{"key":"68_CR181","doi-asserted-by":"crossref","unstructured":"Barr RS, Golden BL, Kelly JP, Resende MGC, Stewart WR (1995) Designing and reporting on computational experiments with heuristic methods. J Heuristics\u00a01(1):9\u201332","DOI":"10.1007\/BF02430363"},{"key":"68_CR182","doi-asserted-by":"crossref","unstructured":"Hooker JN (1995) Testing heuristics: We have it all wrong. J Heuristics\u00a01(1):33\u201342","DOI":"10.1007\/BF02430364"},{"key":"68_CR183","unstructured":"Tufte ER (2001)\u00a0The visual display of quantitative information.\u00a0Graphics press Cheshire, CT,\u00a0vol 2"},{"key":"68_CR184","unstructured":"Chiarandini M, Paquete L, Preuss M, Ridge E (2007) Experiments on metaheuristics: Methodological overview and open issues. Tech Rep DMF-2007-03-003"},{"key":"68_CR185","doi-asserted-by":"crossref","unstructured":"Clerc M (1999) The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. In Proceedings of the 1999 congress on evolutionary computation-CEC99 (Cat. No. 99TH8406).\u00a0IEEE, vol 3, pp\u00a01951\u20131957","DOI":"10.1109\/CEC.1999.785513"},{"key":"68_CR186","doi-asserted-by":"crossref","unstructured":"Birattari M, Kacprzyk J (2009) Tuning metaheuristics: a machine learning perspective.\u00a0Springer, vol 197","DOI":"10.1007\/978-3-642-00483-4_7"},{"key":"68_CR187","doi-asserted-by":"crossref","unstructured":"Blum C, Puchinger J, Raidl GR, Roli A (2011) Hybrid metaheuristics in combinatorial optimization: A survey. Appl Soft Comput 11(6):4135\u20134151","DOI":"10.1016\/j.asoc.2011.02.032"},{"key":"68_CR188","doi-asserted-by":"crossref","unstructured":"S\u00f6rensen K (2015) Metaheuristics\u2013the metaphor exposed. Int Trans Oper Res\u00a022(1), 3\u201318","DOI":"10.1111\/itor.12001"},{"key":"68_CR189","doi-asserted-by":"crossref","unstructured":"Burke EK, Curtois T, Kendall G, Hyde M, Ochoa G, Vazquez-Rodriguez JA (2009) Towards the decathlon challenge of search heuristics. In Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers.\u00a0pp 2205\u20132208","DOI":"10.1145\/1570256.1570303"}],"container-title":["Operations Research Forum"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43069-021-00068-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s43069-021-00068-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43069-021-00068-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,12]],"date-time":"2023-11-12T20:53:36Z","timestamp":1699822416000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s43069-021-00068-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,16]]},"references-count":189,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,9]]}},"alternative-id":["68"],"URL":"https:\/\/doi.org\/10.1007\/s43069-021-00068-x","relation":{},"ISSN":["2662-2556"],"issn-type":[{"value":"2662-2556","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,16]]},"assertion":[{"value":"5 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interestOn behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}],"article-number":"36"}}