{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,18]],"date-time":"2025-05-18T20:41:11Z","timestamp":1747600871235},"reference-count":103,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T00:00:00Z","timestamp":1626220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T00:00:00Z","timestamp":1626220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s12652-021-03269-8","type":"journal-article","created":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T08:03:56Z","timestamp":1626249836000},"page":"5829-5846","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Trigonometric mutation and successful-parent-selection based adaptive asynchronous differential evolution"],"prefix":"10.1007","volume":"13","author":[{"given":"Vaishali","family":"Yadav","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashwani Kumar","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manjit","family":"Kaur","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dilbag","family":"Singh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,7,14]]},"reference":[{"key":"3269_CR1","doi-asserted-by":"publisher","first-page":"100802","DOI":"10.1016\/j.swevo.2020.100802","volume":"60","author":"M Alinaghian","year":"2021","unstructured":"Alinaghian M, Tirkolaee EB, Dezaki ZK, Hejazi SR, Ding W (2021) An augmented Tabu search algorithm for the green inventory-routing problem with time windows. Swarm Evol Comput 60:100802","journal-title":"Swarm Evol Comput"},{"key":"3269_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012064155-0\/50012-4","volume-title":"Introduction to optimum design","author":"JS Arora","year":"2004","unstructured":"Arora JS (2004) Introduction to optimum design. Elsevier"},{"key":"3269_CR3","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1016\/j.amc.2014.01.041","volume":"231","author":"M Asafuddoula","year":"2014","unstructured":"Asafuddoula M, Ray T, Sarker R (2014) An adaptive hybrid differential evolution algorithm for single objective optimization. Appl Math Comput 231:601\u2013618","journal-title":"Appl Math Comput"},{"key":"3269_CR4","unstructured":"Awad NH, Ali MZ, Liang JJ, Qu BY, Suganthan PN (2016) Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization. Tech Rep."},{"key":"3269_CR5","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.ins.2016.10.039","volume":"378","author":"NH Awad","year":"2017","unstructured":"Awad NH, Ali MZ, Suganthan PN, Reynolds RG (2017) CADE: a hybridization of cultural algorithm and differential evolution for numerical optimization. Inf Sci 378:215\u2013241","journal-title":"Inf Sci"},{"issue":"2","key":"3269_CR6","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1007\/s00366-019-00729-w","volume":"36","author":"MS Azqandi","year":"2020","unstructured":"Azqandi MS, Delavar M, Arjmand M (2020) An enhanced time evolutionary optimization for solving engineering design problems. Eng Comput 36(2):763\u2013781","journal-title":"Eng Comput"},{"key":"3269_CR7","doi-asserted-by":"crossref","unstructured":"Bairathi D, Gopalani D (2018) Opposition based salp swarm algorithm for numerical optimization. In:\u00a0International Conference on Intelligent Systems Design and Applications\u00a0(pp. 821\u2013831). Springer, Cham.","DOI":"10.1007\/978-3-030-16660-1_80"},{"issue":"1","key":"3269_CR8","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1049\/trit.2019.0028","volume":"5","author":"HS Basavegowda","year":"2020","unstructured":"Basavegowda HS, Dagnew G (2020) Deep learning approach for microarray cancer data classification. CAAI Trans Intell Technol 5(1):22\u201333","journal-title":"CAAI Trans Intell Technol"},{"key":"3269_CR9","doi-asserted-by":"crossref","unstructured":"Belegundu AD, Arora JS (1985) A study of mathematical programming methods for structural optimization. Part I: theory.\u00a0Int J Numer Methods Eng 21(9): 1583\u20131599","DOI":"10.1002\/nme.1620210904"},{"key":"3269_CR10","doi-asserted-by":"publisher","first-page":"103479","DOI":"10.1016\/j.engappai.2020.103479","volume":"90","author":"PM Bilal","year":"2020","unstructured":"Bilal PM, Zaheer H, Garcia-Hernandez L, Abraham A (2020) Differential evolution: a review of more than two decades of research. Eng Appl Artif Intell 90:103479","journal-title":"Eng Appl Artif Intell"},{"issue":"15","key":"3269_CR11","doi-asserted-by":"publisher","first-page":"6197","DOI":"10.1007\/s00500-018-3273-z","volume":"23","author":"N Bilel","year":"2019","unstructured":"Bilel N, Mohamed N, Zouhaier A, Lotfi R (2019) An efficient evolutionary algorithm for engineering design problems. Soft Comput 23(15):6197\u20136213","journal-title":"Soft Comput"},{"issue":"6","key":"3269_CR12","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1109\/TEVC.2006.872133","volume":"10","author":"J Brest","year":"2006","unstructured":"Brest J, Greiner S, Boskovic B, Mernik M, Zumer V (2006) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6):646\u2013657","journal-title":"IEEE Trans Evol Comput"},{"key":"3269_CR13","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.knosys.2017.10.011","volume":"139","author":"K Chen","year":"2018","unstructured":"Chen K, Zhou F, Liu A (2018a) Chaotic dynamic weight particle swarm optimization for numerical function optimization. Knowl-Based Syst 139:23\u201340","journal-title":"Knowl-Based Syst"},{"key":"3269_CR14","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.asoc.2018.09.007","volume":"73","author":"K Chen","year":"2018","unstructured":"Chen K, Zhou F, Wang Y, Yin L (2018b) An ameliorated particle swarm optimizer for solving numerical optimization problems. Appl Soft Comput 73:482\u2013496","journal-title":"Appl Soft Comput"},{"key":"3269_CR15","doi-asserted-by":"crossref","unstructured":"Choi TJ, Lee Y (2018) Asynchronous differential evolution with selfadaptive parameter control for global numerical optimization. In:\u00a0MATEC Web of Conferences\u00a0(Vol. 189, p. 03020). EDP Sciences.","DOI":"10.1051\/matecconf\/201818903020"},{"key":"3269_CR16","doi-asserted-by":"crossref","unstructured":"Chourasia S, Sharma H, Singh M, Bansal JC (2019) Global and local neighborhood based particle swarm optimization. In:\u00a0Harmony Search and Nature Inspired Optimization Algorithms\u00a0(pp. 449\u2013460). Springer, Singapore","DOI":"10.1007\/978-981-13-0761-4_44"},{"issue":"2","key":"3269_CR17","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/S0166-3615(99)00046-9","volume":"41","author":"CAC Coello","year":"2000","unstructured":"Coello CAC (2000) Use of a self-adaptive penalty approach for engineering optimization problems. Comput Ind 41(2):113\u2013127","journal-title":"Comput Ind"},{"issue":"11\u201312","key":"3269_CR18","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/S0045-7825(01)00323-1","volume":"191","author":"CAC Coello","year":"2002","unstructured":"Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Methods Appl Mech Eng 191(11\u201312):1245\u20131287. https:\/\/doi.org\/10.1016\/S0045-7825(01)00323-1","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"3","key":"3269_CR19","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/S1474-0346(02)00011-3","volume":"16","author":"CAC Coello","year":"2002","unstructured":"Coello CAC, Montes EM (2002) Constraint-handling in genetic algorithms through the use of dominance-based tournament selection. Adv Eng Inform 16(3):193\u2013203","journal-title":"Adv Eng Inform"},{"issue":"4","key":"3269_CR20","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1080\/02630250008970288","volume":"17","author":"CA Coello Coello","year":"2000","unstructured":"Coello Coello CA (2000) Constraint-handling using an evolutionary multiobjective optimization technique. Civil Eng Syst 17(4):319\u2013346","journal-title":"Civil Eng Syst"},{"key":"3269_CR21","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.cor.2015.09.006","volume":"67","author":"L Cui","year":"2016","unstructured":"Cui L, Li G, Lin Q, Chen J, Lu N (2016) Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations. Comput Oper Res 67:155\u2013173","journal-title":"Comput Oper Res"},{"issue":"3","key":"3269_CR22","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/TEVC.2008.2009457","volume":"13","author":"S Das","year":"2009","unstructured":"Das S, Abraham A, Chakraborty UK, Konar A (2009) Differential evolution using a neighborhood-based mutation operator. IEEE Trans Evol Comput 13(3):526\u2013553","journal-title":"IEEE Trans Evol Comput"},{"issue":"2\u20134","key":"3269_CR23","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/S0045-7825(99)00389-8","volume":"186","author":"K Deb","year":"2000","unstructured":"Deb K (2000) An efficient constraint handling method for genetic algorithms. Comput Methods Appl Mech Eng 186(2\u20134):311\u2013338","journal-title":"Comput Methods Appl Mech Eng"},{"key":"3269_CR24","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.advengsoft.2017.05.014","volume":"114","author":"G Dhiman","year":"2017","unstructured":"Dhiman G, Kumar V (2017) Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications. Adv Eng Softw 114:48\u201370","journal-title":"Adv Eng Softw"},{"issue":"5","key":"3269_CR25","doi-asserted-by":"publisher","first-page":"3861","DOI":"10.1007\/s00500-019-04154-5","volume":"24","author":"M Di Carlo","year":"2020","unstructured":"Di Carlo M, Vasile M, Minisci E (2020) Adaptive multi-population inflationary differential evolution. Soft Comput 24(5):3861\u20133891","journal-title":"Soft Comput"},{"issue":"2","key":"3269_CR26","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/s10489-018-1267-2","volume":"49","author":"M Duan","year":"2019","unstructured":"Duan M, Yang H, Liu H, Chen J (2019) A differential evolution algorithm with dual preferred learning mutation. Appl Intell 49(2):605\u2013627","journal-title":"Appl Intell"},{"issue":"2","key":"3269_CR27","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1109\/4235.771166","volume":"3","author":"\u00c1E Eiben","year":"1999","unstructured":"Eiben \u00c1E, Hinterding R, Michalewicz Z (1999) Parameter control in evolutionary algorithms. IEEE Trans Evol Comput 3(2):124\u2013141","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"3269_CR28","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1109\/TEVC.2010.2083670","volume":"15","author":"MG Epitropakis","year":"2011","unstructured":"Epitropakis MG, Tasoulis DK, Pavlidis NG, Plagianakos VP, Vrahatis MN (2011) Enhancing differential evolution utilizing proximity-based mutation operators. IEEE Trans Evol Comput 15(1):99\u2013119","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"3269_CR29","doi-asserted-by":"publisher","first-page":"3091","DOI":"10.1007\/s13369-019-04285-9","volume":"45","author":"HN Fakhouri","year":"2020","unstructured":"Fakhouri HN, Hudaib A, Sleit A (2020) Hybrid particle swarm optimization with sine cosine algorithm and nelder-mead simplex for solving engineering design problems. Arab J Sci Eng 45(4):3091\u20133109","journal-title":"Arab J Sci Eng"},{"issue":"1","key":"3269_CR30","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1023\/A:1024653025686","volume":"27","author":"HY Fan","year":"2003","unstructured":"Fan HY, Lampinen J (2003) A trigonometric mutation operation to differential evolution. J Global Optim 27(1):105\u2013129","journal-title":"J Global Optim"},{"key":"3269_CR31","doi-asserted-by":"crossref","unstructured":"Gandomi AH, Yang XS (2011) Benchmark problems in structural optimization. In:\u00a0Computational optimization, methods and algorithms\u00a0(pp. 259\u2013281). Springer, Berlin, Heidelberg","DOI":"10.1007\/978-3-642-20859-1_12"},{"issue":"1","key":"3269_CR32","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1049\/trit.2019.0051","volume":"5","author":"S Ghosh","year":"2020","unstructured":"Ghosh S, Shivakumara P, Roy P, Pal U, Lu T (2020) Graphology based handwritten character analysis for human behaviour identification. CAAI Trans Intell Technol 5(1):55\u201365","journal-title":"CAAI Trans Intell Technol"},{"issue":"5","key":"3269_CR33","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1109\/TEVC.2014.2375933","volume":"19","author":"SM Guo","year":"2014","unstructured":"Guo SM, Yang CC, Hsu PH, Tsai JSH (2014) Improving differential evolution with a successful-parent-selecting framework. IEEE Trans Evol Comput 19(5):717\u2013730","journal-title":"IEEE Trans Evol Comput"},{"key":"3269_CR34","doi-asserted-by":"crossref","unstructured":"Guo SM, Tsai JSH, Yang CC, Hsu PH (2015) A self-optimization approach for L-SHADE incorporated with eigenvector-based crossover and successful-parent-selecting framework on CEC 2015 benchmark set. In:\u00a02015 IEEE congress on evolutionary computation (CEC)\u00a0(pp. 1003\u20131010). IEEE","DOI":"10.1109\/CEC.2015.7256999"},{"issue":"2","key":"3269_CR35","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1049\/trit.2018.1006","volume":"4","author":"B Gupta","year":"2019","unstructured":"Gupta B, Tiwari M, Lamba SS (2019) Visibility improvement and mass segmentation of mammogram images using quantile separated histogram equalisation with local contrast enhancement. CAAI Trans Intell Technol 4(2):73\u201379","journal-title":"CAAI Trans Intell Technol"},{"key":"3269_CR36","doi-asserted-by":"crossref","unstructured":"Gupta S, Deep K, Moayedi H, Foong LK, Assad A (2020) Sine cosine grey wolf optimizer to solve engineering design problems.\u00a0Eng Comput: 1\u201327.","DOI":"10.1007\/s00366-020-00996-y"},{"issue":"1","key":"3269_CR37","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.engappai.2006.03.003","volume":"20","author":"Q He","year":"2007","unstructured":"He Q, Wang L (2007) An effective co-evolutionary particle swarm optimization for constrained engineering design problems. Eng Appl Artif Intell 20(1):89\u201399","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"3269_CR38","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.amc.2006.07.105","volume":"186","author":"FZ Huang","year":"2007","unstructured":"Huang FZ, Wang L, He Q (2007) An effective co-evolutionary differential evolution for constrained optimization. Appl Math Comput 186(1):340\u2013356","journal-title":"Appl Math Comput"},{"issue":"2\u20134","key":"3269_CR39","first-page":"278","volume":"13","author":"KK Kaleka","year":"2020","unstructured":"Kaleka KK, Kaur A, Kumar V (2020) A conceptual comparison of metaheuristic algorithms and applications to engineering design problems. Int J Intell Inf Database Syst 13(2\u20134):278\u2013306","journal-title":"Int J Intell Inf Database Syst"},{"issue":"2","key":"3269_CR40","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1115\/1.2919393","volume":"116","author":"BK Kannan","year":"1994","unstructured":"Kannan BK, Kramer SN (1994) An augmented Lagrange multiplier-based method for mixed integer discrete continuous optimization and its applications to mechanical design. J Mech Des 116(2):405\u2013411","journal-title":"J Mech Des"},{"issue":"2","key":"3269_CR41","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1109\/TEVC.2014.2308294","volume":"19","author":"G Karafotias","year":"2014","unstructured":"Karafotias G, Hoogendoorn M, Eiben \u00c1E (2014) Parameter control in evolutionary algorithms: trends and challenges. IEEE Trans Evol Comput 19(2):167\u2013187","journal-title":"IEEE Trans Evol Comput"},{"key":"3269_CR42","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1108\/02644401011008577","volume":"27","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) An improved ant colony optimization for constrained engineering design problems. Eng Comput 27:155\u2013182","journal-title":"Eng Comput"},{"issue":"5","key":"3269_CR43","doi-asserted-by":"publisher","first-page":"1699","DOI":"10.1007\/s00500-017-2894-y","volume":"23","author":"S Khalilpourazari","year":"2019","unstructured":"Khalilpourazari S, Khalilpourazary S (2019) An efficient hybrid algorithm based on water cycle and moth-flame optimization algorithms for solving numerical and constrained engineering optimization problems. Soft Comput 23(5):1699\u20131722","journal-title":"Soft Comput"},{"key":"3269_CR44","doi-asserted-by":"crossref","unstructured":"Khalilpourazari S, Pasandideh SHR (2019) Sine\u2013cosine crow search algorithm: theory and applications.\u00a0Neural Comput Appl: 1\u201318.","DOI":"10.1007\/s00521-019-04530-0"},{"key":"3269_CR45","doi-asserted-by":"crossref","unstructured":"Kizilay D, Tasgetiren MF, Oztop H, Kandiller L, Suganthan PN (2020) A differential evolution algorithm with q-learning for solving engineering design problems. In:\u00a02020 IEEE Congress on Evolutionary Computation (CEC)\u00a0(pp. 1\u20138). IEEE","DOI":"10.1109\/CEC48606.2020.9185743"},{"key":"3269_CR46","doi-asserted-by":"crossref","unstructured":"Konar A, Saha S (2018) Differential evolution based dance composition. In:\u00a0Gesture Recognition\u00a0(pp. 225\u2013241). Springer, Cham.","DOI":"10.1007\/978-3-319-62212-5_7"},{"issue":"2","key":"3269_CR47","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.jcde.2018.08.003","volume":"6","author":"H Koyuncu","year":"2019","unstructured":"Koyuncu H, Ceylan R (2019) A PSO based approach: scout particle swarm algorithm for continuous global optimization problems. J Comput Design Eng 6(2):129\u2013142","journal-title":"J Comput Design Eng"},{"issue":"10","key":"3269_CR48","doi-asserted-by":"publisher","first-page":"6449","DOI":"10.1007\/s00521-018-3454-9","volume":"31","author":"X Lai","year":"2019","unstructured":"Lai X, Zhou Y (2019) An adaptive parallel particle swarm optimization for numerical optimization problems. Neural Comput Appl 31(10):6449\u20136467","journal-title":"Neural Comput Appl"},{"issue":"36\u201338","key":"3269_CR49","doi-asserted-by":"publisher","first-page":"3902","DOI":"10.1016\/j.cma.2004.09.007","volume":"194","author":"KS Lee","year":"2005","unstructured":"Lee KS, Geem ZW (2005) A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput Methods Appl Mech Eng 194(36\u201338):3902\u20133933","journal-title":"Comput Methods Appl Mech Eng"},{"key":"3269_CR50","doi-asserted-by":"crossref","unstructured":"Li S, Gu Q, Gong W, Ning B (2020) An enhanced adaptive differential evolution algorithm for parameter extraction of photovoltaic models. Energy Conv Manag 205(112443)","DOI":"10.1016\/j.enconman.2019.112443"},{"key":"3269_CR51","unstructured":"Liang JJ, Qu BY, Suganthan PN, Chen Q (2014) Problem definitions and evaluation criteria for the CEC 2015 competition on learning-based real-parameter single objective optimization.\u00a0Technical Report201411A, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore,\u00a029, 625\u2013640"},{"issue":"1","key":"3269_CR52","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s11633-016-0990-6","volume":"15","author":"GH Lin","year":"2018","unstructured":"Lin GH, Zhang J, Liu ZH (2018) Hybrid particle swarm optimization with differential evolution for numerical and engineering optimization. Int J Autom Comput 15(1):103\u2013114","journal-title":"Int J Autom Comput"},{"key":"3269_CR53","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1016\/j.swevo.2018.07.002","volume":"44","author":"A Lin","year":"2019","unstructured":"Lin A, Sun W, Yu H, Wu G, Tang H (2019) Global genetic learning particle swarm optimization with diversity enhancement by ring topology. Swarm Evol Comput 44:571\u2013583","journal-title":"Swarm Evol Comput"},{"issue":"6","key":"3269_CR54","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1007\/s00500-004-0363-x","volume":"9","author":"J Liu","year":"2005","unstructured":"Liu J, Lampinen J (2005) A fuzzy adaptive differential evolution algorithm. Soft Comput 9(6):448\u2013462","journal-title":"Soft Comput"},{"key":"3269_CR55","doi-asserted-by":"crossref","unstructured":"Liu Z, Nishi T (2020) Multipopulation ensemble particle swarm optimizer for engineering design problems.\u00a0Math Prob Eng","DOI":"10.1155\/2020\/1450985"},{"issue":"5","key":"3269_CR56","doi-asserted-by":"publisher","first-page":"1982","DOI":"10.1007\/s10489-018-1362-4","volume":"49","author":"J Luo","year":"2019","unstructured":"Luo J, Shi B (2019) A hybrid whale optimization algorithm based on modified differential evolution for global optimization problems. Appl Intell 49(5):1982\u20132000","journal-title":"Appl Intell"},{"issue":"2","key":"3269_CR57","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1016\/j.asoc.2010.04.024","volume":"11","author":"R Mallipeddi","year":"2011","unstructured":"Mallipeddi R, Suganthan PN, Pan QK, Tasgetiren MF (2011) Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl Soft Comput 11(2):1679\u20131696","journal-title":"Appl Soft Comput"},{"key":"3269_CR58","doi-asserted-by":"publisher","first-page":"12832","DOI":"10.1109\/ACCESS.2019.2893292","volume":"7","author":"Z Meng","year":"2019","unstructured":"Meng Z, Pan JS (2019) HARD-DE: Hierarchical archive based mutation strategy with depth information of evolution for the enhancement of differential evolution on numerical optimization. IEEE Access 7:12832\u201312854","journal-title":"IEEE Access"},{"key":"3269_CR59","doi-asserted-by":"publisher","first-page":"51145","DOI":"10.1109\/ACCESS.2020.2979738","volume":"8","author":"Z Meng","year":"2020","unstructured":"Meng Z, Chen Y, Li X (2020a) Enhancing differential evolution with novel parameter control. IEEE Access 8:51145\u201351167","journal-title":"IEEE Access"},{"key":"3269_CR60","doi-asserted-by":"publisher","first-page":"40809","DOI":"10.1109\/ACCESS.2020.2976845","volume":"8","author":"Z Meng","year":"2020","unstructured":"Meng Z, Yang C, Li X, Chen Y (2020b) Di-DE: depth information-based differential evolution with adaptive parameter control for numerical optimization. IEEE Access 8:40809\u201340827","journal-title":"IEEE Access"},{"key":"3269_CR61","doi-asserted-by":"crossref","unstructured":"Mezura-Montes E, Coello CAC (2005) Useful infeasible solutions in engineering optimization with evolutionary algorithms. In:\u00a0Mexican international conference on artificial intelligence\u00a0(pp. 652\u2013662). Springer, Berlin, Heidelberg","DOI":"10.1007\/11579427_66"},{"key":"3269_CR62","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Adv Eng Softw"},{"key":"3269_CR63","doi-asserted-by":"crossref","unstructured":"Noman N, Bollegala D, Iba H (2011) An adaptive differential evolution algorithm. In:\u00a02011 IEEE Congress of Evolutionary Computation (CEC)\u00a0(pp. 2229\u20132236). IEEE.","DOI":"10.1109\/CEC.2011.5949891"},{"key":"3269_CR64","doi-asserted-by":"crossref","unstructured":"Omran MG, Salman A, Engelbrecht AP (2005) Self-adaptive differential evolution. In:\u00a0International conference on computational and information science\u00a0(pp. 192\u2013199). Springer, Berlin, Heidelberg.","DOI":"10.1007\/11596448_28"},{"issue":"1","key":"3269_CR65","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1504\/IJHM.2019.098951","volume":"2","author":"S Osterland","year":"2019","unstructured":"Osterland S, Weber J (2019) Analytical analysis of single-stage pressure relief valves. Int J Hydromech 2(1):32\u201353","journal-title":"Int J Hydromech"},{"key":"3269_CR66","doi-asserted-by":"publisher","first-page":"17691","DOI":"10.1109\/ACCESS.2020.2968119","volume":"8","author":"JS Pan","year":"2020","unstructured":"Pan JS, Liu N, Chu SC (2020a) A hybrid differential evolution algorithm and its application in unmanned combat aerial vehicle path planning. IEEE Access 8:17691\u201317712","journal-title":"IEEE Access"},{"issue":"1","key":"3269_CR67","first-page":"1","volume":"38","author":"JS Pan","year":"2020","unstructured":"Pan JS, Yang C, Meng F, Chen Y, Meng Z (2020b) A parameter adaptive DE algorithm on real-parameter optimization. J Intell Fuzzy Syst 38(1):1\u201312","journal-title":"J Intell Fuzzy Syst"},{"issue":"2","key":"3269_CR68","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2008","unstructured":"Qin AK, Huang VL, Suganthan PN (2008) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13(2):398\u2013417","journal-title":"IEEE Trans Evol Comput"},{"key":"3269_CR69","first-page":"181","volume":"9","author":"J Rajpurohit","year":"2017","unstructured":"Rajpurohit J, Sharma TK, Abraham A, Vaishali A (2017) Glossary of metaheuristic algorithms. Int J Comput Inf Syst Ind Manag Appl 9:181\u2013205","journal-title":"Int J Comput Inf Syst Ind Manag Appl"},{"issue":"1","key":"3269_CR70","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1108\/WJE-09-2019-0254","volume":"17","author":"SA Rather","year":"2020","unstructured":"Rather SA, Bala PS (2020) Swarm-based chaotic gravitational search algorithm for solving mechanical engineering design problems. World J Eng 17(1):97\u2013114","journal-title":"World J Eng"},{"key":"3269_CR71","doi-asserted-by":"publisher","first-page":"812","DOI":"10.1016\/j.asoc.2016.09.042","volume":"52","author":"H Salehinejad","year":"2017","unstructured":"Salehinejad H, Rahnamayan S, Tizhoosh HR (2017) Micro-differential evolution: diversity enhancement and a comparative study. Appl Soft Comput 52:812\u2013833","journal-title":"Appl Soft Comput"},{"key":"3269_CR72","doi-asserted-by":"crossref","unstructured":"Sallam KM, Sarker RA, Essam DL, Elsayed SM (2015) Neurodynamic differential evolution algorithm and solving CEC2015 competition problems. In:\u00a02015 IEEE Congress on Evolutionary Computation (CEC)\u00a0(pp. 1033\u20131040). IEEE.","DOI":"10.1109\/CEC.2015.7257003"},{"key":"3269_CR73","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1016\/j.asoc.2018.04.027","volume":"69","author":"R Santos","year":"2018","unstructured":"Santos R, Borges G, Santos A, Silva M, Sales C, Costa JC (2018) A semi-autonomous particle swarm optimizer based on gradient information and diversity control for global optimization. Appl Soft Comput 69:330\u2013343","journal-title":"Appl Soft Comput"},{"issue":"5","key":"3269_CR74","doi-asserted-by":"publisher","first-page":"2395","DOI":"10.1007\/s11227-018-2625-x","volume":"75","author":"M Shehab","year":"2019","unstructured":"Shehab M, Khader AT, Laouchedi M, Alomari OA (2019) Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization. J Supercomput 75(5):2395\u20132422","journal-title":"J Supercomput"},{"key":"3269_CR75","doi-asserted-by":"publisher","first-page":"100463","DOI":"10.1016\/j.swevo.2018.10.014","volume":"50","author":"V Stanovov","year":"2019","unstructured":"Stanovov V, Akhmedova S, Semenkin E (2019) Selective pressure strategy in differential evolution: exploitation improvement in solving global optimization problems. Swarm Evol Comput 50:100463","journal-title":"Swarm Evol Comput"},{"key":"3269_CR76","unstructured":"Storn R, Price K (1995) Differential evolution\u2014a simple and efficient heuristic for global optimization over continuous spaces (Tech. Rep.), Berkeley, CA. TR-95\u2013012."},{"key":"3269_CR77","doi-asserted-by":"crossref","unstructured":"Sun G, Yang B, Yang Z, Xu G (2019) An adaptive differential evolution with combined strategy for global numerical optimization.\u00a0Soft Comput: 1\u201320.","DOI":"10.1007\/s00500-019-03934-3"},{"key":"3269_CR78","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1016\/j.apm.2020.07.052","volume":"89","author":"P Sun","year":"2021","unstructured":"Sun P, Liu H, Zhang Y, Tu L, Meng Q (2021) An intensify atom search optimization for engineering design problems. Appl Math Model 89:837\u2013859","journal-title":"Appl Math Model"},{"key":"3269_CR79","doi-asserted-by":"publisher","first-page":"106560","DOI":"10.1016\/j.cie.2020.106560","volume":"145","author":"S Talatahari","year":"2020","unstructured":"Talatahari S, Azizi M (2020) Optimization of constrained mathematical and engineering design problems using chaos game optimization. Comput Ind Eng 145:106560","journal-title":"Comput Ind Eng"},{"issue":"5","key":"3269_CR80","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1080\/00207160.2018.1463438","volume":"96","author":"JH Tam","year":"2019","unstructured":"Tam JH, Ong ZC, Ismail Z, Ang BC, Khoo SY (2019) A new hybrid GA\u2212ACO\u2212PSO algorithm for solving various engineering design problems. Int J Comput Math 96(5):883\u2013919","journal-title":"Int J Comput Math"},{"key":"3269_CR81","doi-asserted-by":"crossref","unstructured":"Tanabe R, Fukunaga A (2013) Success-history based parameter adaptation for differential evolution. In:\u00a02013 IEEE congress on evolutionary computation\u00a0(pp. 71\u201378). IEEE.","DOI":"10.1109\/CEC.2013.6557555"},{"key":"3269_CR82","doi-asserted-by":"crossref","unstructured":"Tanabe R, Fukunaga AS (2014) Improving the search performance of SHADE using linear population size reduction. In:\u00a02014 IEEE congress on evolutionary computation (CEC)\u00a0(pp. 1658\u20131665). IEEE.","DOI":"10.1109\/CEC.2014.6900380"},{"key":"3269_CR83","unstructured":"Thangaraj R, Pant M, Abraham A (2009) A simple adaptive differential evolution algorithm. In:\u00a02009 world congress on nature and biologically inspired computing (NaBIC)\u00a0(pp. 457\u2013462). IEEE."},{"key":"3269_CR84","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.ins.2018.11.021","volume":"478","author":"M Tian","year":"2019","unstructured":"Tian M, Gao X (2019) Differential evolution with neighborhood-based adaptive evolution mechanism for numerical optimization. Inf Sci 478:422\u2013448","journal-title":"Inf Sci"},{"issue":"11","key":"3269_CR85","doi-asserted-by":"publisher","first-page":"2772","DOI":"10.1109\/TFUZZ.2020.2998174","volume":"28","author":"EB Tirkolaee","year":"2020","unstructured":"Tirkolaee EB, Goli A, Weber GW (2020) Fuzzy mathematical programming and self-adaptive artificial fish swarm algorithm for just-in-time energy-aware flow shop scheduling problem with outsourcing option. IEEE Trans Fuzzy Syst 28(11):2772\u20132783. https:\/\/doi.org\/10.1109\/TFUZZ.2020.2998174","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"3269_CR86","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.neucom.2018.02.038","volume":"290","author":"L Tong","year":"2018","unstructured":"Tong L, Dong M, Jing C (2018) An improved multi-population ensemble differential evolution. Neurocomputing 290:130\u2013147","journal-title":"Neurocomputing"},{"key":"3269_CR87","doi-asserted-by":"crossref","unstructured":"Vaishali Sharma TK (2016) Asynchronous differential evolution with convex mutation. In:\u00a0Proceedings of fifth international conference on soft computing for problem solving\u00a0(pp. 915\u2013928). Springer, Singapore.","DOI":"10.1007\/978-981-10-0451-3_81"},{"key":"3269_CR88","doi-asserted-by":"crossref","unstructured":"Vaishali Sharma TK, Abraham A, Rajpurohit J (2018a) Trigonometric probability tuning in asynchronous differential evolution. In:\u00a0Soft Computing: Theories and Applications\u00a0(pp. 267\u2013278). Springer, Singapore.","DOI":"10.1007\/978-981-10-5699-4_26"},{"key":"3269_CR89","doi-asserted-by":"crossref","unstructured":"Vaishali Sharma TK, Abraham A, Rajpurohit J (2018b) Enhanced asynchronous differential evolution using trigonometric mutation. In:\u00a0Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016), AISC\u00a0(Vol. 614), (pp. 386\u2013397). Springer, Cham","DOI":"10.1007\/978-3-319-60618-7_38"},{"issue":"1","key":"3269_CR90","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/TEVC.2010.2087271","volume":"15","author":"Y Wang","year":"2011","unstructured":"Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evol Comput 15(1):55\u201366","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"3269_CR91","doi-asserted-by":"publisher","first-page":"286","DOI":"10.18178\/ijmlc.2018.8.3.701","volume":"8","author":"SL Wang","year":"2018","unstructured":"Wang SL, Ng TF, Morsidi F (2018) Self-adaptive ensemble based differential evolution. Int J Mach Learn Comput 8(3):286\u2013293","journal-title":"Int J Mach Learn Comput"},{"key":"3269_CR92","doi-asserted-by":"publisher","first-page":"105496","DOI":"10.1016\/j.asoc.2019.105496","volume":"81","author":"S Wang","year":"2019","unstructured":"Wang S, Li Y, Yang H (2019) Self-adaptive mutation differential evolution algorithm based on particle swarm optimization. Appl Soft Comput 81:105496","journal-title":"Appl Soft Comput"},{"issue":"3","key":"3269_CR93","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1504\/IJHM.2019.102893","volume":"2","author":"R Wang","year":"2019","unstructured":"Wang R, Yu H, Wang G, Zhang G, Wang W (2019) Study on the dynamic and static characteristics of gas static thrust bearing with micro-hole restrictors. Int J Hydromech 2(3):189\u2013202","journal-title":"Int J Hydromech"},{"issue":"1","key":"3269_CR94","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1504\/IJHM.2019.098949","volume":"2","author":"T Wiens","year":"2019","unstructured":"Wiens T (2019) Engine speed reduction for hydraulic machinery using predictive algorithms. Int J Hydromech 2(1):16\u201331","journal-title":"Int J Hydromech"},{"key":"3269_CR95","doi-asserted-by":"publisher","first-page":"285730","DOI":"10.1155\/2015\/285730","volume":"2015","author":"WL Xiang","year":"2015","unstructured":"Xiang WL, Meng XL, An MQ, Li YZ, Gao MX (2015) An enhanced differential evolution algorithm based on multiple mutation strategies. Comput Intell Neurosci 2015:285730","journal-title":"Comput Intell Neurosci"},{"key":"3269_CR96","doi-asserted-by":"crossref","unstructured":"Zhabitskaya E, Zhabitsky M (2011) Asynchronous differential evolution. In:\u00a0International Conference on Mathematical Modeling and Computational Physics\u00a0(pp. 328\u2013333). Springer, Berlin, Heidelberg.","DOI":"10.1007\/978-3-642-28212-6_41"},{"key":"3269_CR97","doi-asserted-by":"crossref","unstructured":"Zhabitsky M (2016) Comparison of the asynchronous differential evolution and jade minimization algorithms. In:\u00a0EPJ Web of Conferences\u00a0(Vol. 108, p. 02048). EDP Sciences.","DOI":"10.1051\/epjconf\/201610802048"},{"issue":"5","key":"3269_CR98","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","volume":"13","author":"J Zhang","year":"2009","unstructured":"Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5):945\u2013958","journal-title":"IEEE Trans Evol Comput"},{"issue":"12","key":"3269_CR99","doi-asserted-by":"publisher","first-page":"287","DOI":"10.3390\/math6120287","volume":"6","author":"X Zhang","year":"2018","unstructured":"Zhang X, Zou D, Shen X (2018) A novel simple particle swarm optimization algorithm for global optimization. Mathematics 6(12):287","journal-title":"Mathematics"},{"issue":"8","key":"3269_CR100","doi-asserted-by":"publisher","first-page":"6149","DOI":"10.1007\/s13369-014-1248-7","volume":"39","author":"S Zhao","year":"2014","unstructured":"Zhao S, Wang X, Chen L, Zhu W (2014) A novel self-adaptive differential evolution algorithm with population size adjustment scheme. Arab J Sci Eng 39(8):6149\u20136174","journal-title":"Arab J Sci Eng"},{"issue":"1","key":"3269_CR101","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/s40314-015-0237-0","volume":"36","author":"F Zhao","year":"2017","unstructured":"Zhao F, Shao Z, Wang J, Zhang C (2017) A hybrid optimization algorithm based on chaotic differential evolution and estimation of distribution. Comput Appl Math 36(1):433\u2013458","journal-title":"Comput Appl Math"},{"key":"3269_CR102","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.ins.2017.02.055","volume":"399","author":"LM Zheng","year":"2017","unstructured":"Zheng LM, Zhang SX, Tang KS, Zheng SY (2017) Differential evolution powered by collective information. Inf Sci 399:13\u201329","journal-title":"Inf Sci"},{"key":"3269_CR103","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.ins.2012.09.019","volume":"223","author":"W Zhu","year":"2013","unstructured":"Zhu W, Tang Y, Fang JA, Zhang W (2013) Adaptive population tuning scheme for differential evolution. Inf Sci 223:164\u2013191","journal-title":"Inf Sci"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03269-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-021-03269-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03269-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T01:05:27Z","timestamp":1699232727000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-021-03269-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,14]]},"references-count":103,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["3269"],"URL":"https:\/\/doi.org\/10.1007\/s12652-021-03269-8","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,14]]},"assertion":[{"value":"19 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 April 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 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":"The authors declare no competitive interests regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}