{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T08:30:35Z","timestamp":1748248235292,"version":"3.40.4"},"reference-count":87,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52465059"],"award-info":[{"award-number":["52465059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Incubation Planning Project of Guizhou University","award":["[2020]75"],"award-info":[{"award-number":["[2020]75"]}]},{"name":"Foundation of Key Laboratory of Advanced Manufacturing Technology"},{"name":"Ministry of Education, Guizhou University","award":["GZUAMT2021KF[11]"],"award-info":[{"award-number":["GZUAMT2021KF[11]"]}]},{"name":"Guizhou University Talent Fund","award":["2022]27"],"award-info":[{"award-number":["2022]27"]}]},{"name":"Open Foundation of State Key Laboratory of Public Big Data","award":["PBD.2021-07"],"award-info":[{"award-number":["PBD.2021-07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This paper introduces an enhanced slime mould algorithm (EESMA) designed to address critical challenges in engineering design optimization. The EESMA integrates three novel strategies: the Laplace logistic sine map technique, the adaptive t-distribution elite mutation mechanism, and the ranking-based dynamic learning strategy. These enhancements collectively improve the algorithm\u2019s search efficiency, mitigate convergence to local optima, and bolster robustness in complex optimization tasks. The proposed EESMA demonstrates significant advantages over many conventional optimization algorithms and performs on par with, or even surpasses, several advanced algorithms in benchmark tests. Its superior performance is validated through extensive evaluations on diverse test sets, including IEEE CEC2014, IEEE CEC2020, and IEEE CEC2022, and its successful application in six distinct engineering problems. Notably, EESMA excels in solving economic load dispatch problems, highlighting its capability to tackle challenging optimization scenarios. The results affirm that EESMA is a competitive and effective tool for addressing complex optimization issues, showcasing its potential for widespread application in engineering and beyond.<\/jats:p>","DOI":"10.1093\/jcde\/qwae089","type":"journal-article","created":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T02:50:25Z","timestamp":1729219825000},"page":"36-74","source":"Crossref","is-referenced-by-count":1,"title":["An enhanced slime mould algorithm with triple strategy for engineering design optimization"],"prefix":"10.1093","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8369-7127","authenticated-orcid":false,"given":"Shuai","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang 550025 ,","place":["China"]}]},{"given":"Junxing","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang 550025 ,","place":["China"]},{"name":"Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University , Guiyang 550025 ,","place":["China"]}]},{"given":"Shaobo","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang 550025 ,","place":["China"]},{"name":"Guizhou Institute of Technology , Guiyang 550025 ,","place":["China"]}]},{"given":"Fengbin","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang 550025 ,","place":["China"]}]},{"given":"Shaoyang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Guizhou University , Guiyang 550025 ,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2024,10,17]]},"reference":[{"key":"2025041407274831700_bib1","doi-asserted-by":"publisher","first-page":"104107","DOI":"10.1016\/j.autcon.2021.104107","article-title":"An exponential chaotic differential evolution algorithm for optimizing bridge maintenance plans","volume-title":"Automation in Construction","author":"Abdelkader","year":"2022"},{"key":"2025041407274831700_bib2","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1007\/978-3-319-26662-6_38","article-title":"On creativity of slime mould","volume-title":"Advances in Physarum Machines: Sensing and Computing with Slime Mould","author":"Adamatzky","year":"2016"},{"key":"2025041407274831700_bib3","doi-asserted-by":"publisher","first-page":"115079","DOI":"10.1016\/j.eswa.2021.115079","article-title":"RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method","volume":"181","author":"Ahmadianfar","year":"2021","journal-title":"Expert Systems with Applications"},{"key":"2025041407274831700_bib4","doi-asserted-by":"publisher","first-page":"116516","DOI":"10.1016\/j.eswa.2022.116516","article-title":"INFO: An efficient optimization algorithm based on weighted mean of vectors","volume-title":"Expert Systems with Applications","author":"Ahmadianfar","year":"2022"},{"key":"2025041407274831700_bib5","doi-asserted-by":"publisher","first-page":"11685","DOI":"10.1007\/s12652-022-03731-1","article-title":"Economic load dispatch using memetic sine cosine algorithm","volume":"14","author":"Al-Betar","year":"2022","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"2025041407274831700_bib6","doi-asserted-by":"publisher","first-page":"3904","DOI":"10.3390\/en15113904","article-title":"Greedy Sine-Cosine non-hierarchical grey wolf optimizer for solving non-convex economic load dispatch problems","volume-title":"Energies","author":"Alghamdi","year":"2022"},{"key":"2025041407274831700_bib7","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/s10462-022-10173-w","article-title":"Fire Hawk Optimizer: A novel metaheuristic algorithm","volume":"56","author":"Azizi","year":"2023","journal-title":"Artificial Intelligence Review"},{"key":"2025041407274831700_bib8","doi-asserted-by":"publisher","first-page":"160221","DOI":"10.1109\/ACCESS.2020.3020054","article-title":"Multi-objective optimization algorithm and preference Multi-objective decision-making based on artificial intelligence biological immune system","volume":"8","author":"Bao","year":"2020","journal-title":"IEEE Access"},{"key":"2025041407274831700_bib9","doi-asserted-by":"publisher","first-page":"8548639","DOI":"10.1155\/2021\/8548639","article-title":"Social network search for solving engineering optimization problems","volume":"2021","author":"Bayzidi","year":"2021","journal-title":"Computational Intelligence and Neuroscience"},{"key":"2025041407274831700_bib10","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1016\/0004-3702(89)90050-7","article-title":"Classifier systems and genetic algorithms","volume":"40","author":"Booker","year":"1989","journal-title":"Artificial Intelligence"},{"key":"2025041407274831700_bib11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/CEC48606.2020.9185551","article-title":"Differential evolution algorithm for single objective bound-constrained optimization: Algorithm j2020","author":"Brest","year":"2020","journal-title":"2020 IEEE Congress on Evolutionary Computation (CEC)"},{"key":"2025041407274831700_bib12","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1016\/j.enconman.2019.05.057","article-title":"An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models","volume-title":"Energy Conversion and Management","author":"Chen","year":"2019"},{"key":"2025041407274831700_bib13","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.apm.2019.02.004","article-title":"A balanced whale optimization algorithm for constrained engineering design problems","volume":"71","author":"Chen","year":"2019","journal-title":"Applied Mathematical Modelling"},{"key":"2025041407274831700_bib14","doi-asserted-by":"publisher","first-page":"156851","DOI":"10.1109\/ACCESS.2020.3018866","article-title":"An efficient parameter adaptive support vector regression using K-means clustering and chaotic slime mould algorithm","volume":"8","author":"Chen","year":"2020","journal-title":"IEEE Access"},{"key":"2025041407274831700_bib15","doi-asserted-by":"publisher","first-page":"113875","DOI":"10.1016\/j.eswa.2020.113875","article-title":"Bezier Search differential Evolution Algorithm for numerical function optimization: A comparative study with CRMLSP, MVO, WA, SHADE and LSHADE","volume-title":"Expert Systems with Applications","author":"Civicioglu","year":"2021"},{"key":"2025041407274831700_bib16","doi-asserted-by":"publisher","first-page":"6603","DOI":"10.1007\/s00521-022-08013-7","article-title":"Bernstein-Levy differential evolution algorithm for numerical function optimization","volume-title":"Neural Computing and Applications","author":"Civicioglu","year":"2023"},{"key":"2025041407274831700_bib17","doi-asserted-by":"publisher","first-page":"3923","DOI":"10.1007\/s00521-018-3822-5","article-title":"Weighted differential evolution algorithm for numerical function optimization: A comparative study with cuckoo search, artificial bee colony, adaptive differential evolution, and backtracking search optimization algorithms","volume-title":"Neural Computing and Applications","author":"Civicioglu","year":"2020"},{"key":"2025041407274831700_bib18","doi-asserted-by":"publisher","first-page":"110011","DOI":"10.1016\/j.knosys.2022.110011","article-title":"Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems","volume-title":"Knowledge-Based Systems","author":"Dehghani","year":"2023"},{"key":"2025041407274831700_bib19","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.1999.782657","article-title":"Ant colony optimization: A new meta-heuristic","volume-title":"Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406)","author":"Dorigo","year":"1999"},{"key":"2025041407274831700_bib20","doi-asserted-by":"publisher","DOI":"10.1109\/ISMSIT50672.2020.9254597","article-title":"An application of slime mould algorithm for optimizing parameters of power system stabilizer","volume-title":"2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","author":"Ekinci","year":"2020"},{"key":"2025041407274831700_bib21","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1093\/jcde\/qwac013","article-title":"A hybrid genetic-firefly algorithm for engineering design problems","volume":"9","author":"El-Shorbagy","year":"2022","journal-title":"Journal of Computational Design and Engineering"},{"key":"2025041407274831700_bib22","doi-asserted-by":"publisher","first-page":"105190","DOI":"10.1016\/j.knosys.2019.105190","article-title":"Equilibrium optimizer: A novel optimization algorithm","volume-title":"Knowledge-Based Systems","author":"Faramarzi","year":"2020"},{"key":"2025041407274831700_bib23","doi-asserted-by":"publisher","first-page":"2531","DOI":"10.1007\/s11831-021-09694-4","article-title":"Particle swarm optimization algorithm and its applications: A systematic review","volume":"29","author":"Gad","year":"2022","journal-title":"Archives of Computational Methods in Engineering"},{"key":"2025041407274831700_bib24","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1177\/003754970107600201","article-title":"A new heuristic optimization algorithm: Harmony search","volume":"76","author":"Geem","year":"2001","journal-title":"Simulation"},{"key":"2025041407274831700_bib25","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/0305-0548(86)90048-1","article-title":"Future paths for integer programming and links to artificial intelligence","volume":"13","author":"Glover","year":"1986","journal-title":"Computers & Operations Research"},{"key":"2025041407274831700_bib26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/106365603321828970","article-title":"Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES)","volume":"11","author":"Hansen","year":"2003","journal-title":"Evolutionary Computation"},{"key":"2025041407274831700_bib27","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1007\/s10489-020-01893-z","article-title":"Archimedes optimization algorithm: A new metaheuristic algorithm for solving optimization problems","volume":"51","author":"Hashim","year":"2021","journal-title":"Applied Intelligence"},{"key":"2025041407274831700_bib28","doi-asserted-by":"publisher","first-page":"Article 108320","DOI":"10.1016\/j.knosys.2022.108320","article-title":"Snake Optimizer: A novel meta-heuristic optimization algorithm","volume-title":"Knowledge-Based Systems","author":"Hashim","year":"2022"},{"key":"2025041407274831700_bib29","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.ins.2012.08.023","article-title":"Black hole: A new heuristic optimization approach for data clustering","volume":"222","author":"Hatamlou","year":"2013","journal-title":"Information Sciences"},{"key":"2025041407274831700_bib30","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","article-title":"Harris hawks optimization: Algorithm and applications","volume-title":"Future Generation Computer Systems","author":"Heidari","year":"2019"},{"key":"2025041407274831700_bib31","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/tec.2007.914171","article-title":"An economic dispatch model incorporating wind power","volume":"23","author":"Hetzer","year":"2008","journal-title":"IEEE Transactions on Energy Conversion"},{"key":"2025041407274831700_bib32","doi-asserted-by":"publisher","first-page":"109942","DOI":"10.1016\/j.foodcont.2023.109942","article-title":"Olfactory sensor combined with chemometrics analysis to determine fatty acid in stored wheat","volume":"153","author":"Jiang","year":"2023","journal-title":"Food Control"},{"key":"2025041407274831700_bib33","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","article-title":"A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm","volume":"39","author":"Karaboga","year":"2007","journal-title":"Journal of Global Optimization"},{"key":"2025041407274831700_bib34","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.cor.2014.10.011","article-title":"A new metaheuristic for optimization: Optics inspired optimization (OIO)","volume":"55","author":"Kashan","year":"2015","journal-title":"Computers & Operations Research"},{"key":"2025041407274831700_bib35","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","author":"Kirkpatrick","year":"1983","journal-title":"Science (New York, N.Y.)"},{"key":"2025041407274831700_bib36","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.jcde.2017.02.005","article-title":"Chaotic grey wolf optimization algorithm for constrained optimization problems","volume":"5","author":"Kohli","year":"2018","journal-title":"Journal of Computational Design and Engineering"},{"key":"2025041407274831700_bib37","doi-asserted-by":"publisher","first-page":"100693","DOI":"10.1016\/j.swevo.2020.100693","article-title":"A test-suite of non-convex constrained optimization problems from the real-world and some baseline results","volume-title":"Swarm and Evolutionary Computation","author":"Kumar","year":"2020"},{"key":"2025041407274831700_bib38","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","article-title":"Slime mould algorithm: A new method for stochastic optimization","volume-title":"Future Generation Computer Systems","author":"Li","year":"2020"},{"key":"2025041407274831700_bib39","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/jhep08(2016)106","article-title":"A bound on chaos","volume":"8","author":"Maldacena","year":"2016","journal-title":"Journal of High Energy Physics"},{"key":"2025041407274831700_bib40","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.eswa.2015.10.012","article-title":"A glowworm swarm optimization algorithm for the vehicle routing problem with stochastic demands","volume":"46","author":"Marinaki","year":"2016","journal-title":"Expert Systems with Applications"},{"key":"2025041407274831700_bib41","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","article-title":"The Ant Lion Optimizer","volume-title":"Advances in Engineering Software","author":"Mirjalili","year":"2015"},{"key":"2025041407274831700_bib42","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","article-title":"SCA: A sine Cosine algorithm for solving optimization problems","volume-title":"Knowledge-Based Systems","author":"Mirjalili","year":"2016"},{"key":"2025041407274831700_bib43","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The whale optimization algorithm","volume-title":"Advances in Engineering Software","author":"Mirjalili","year":"2016"},{"key":"2025041407274831700_bib44","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","article-title":"Multi-Verse Optimizer: A nature-inspired algorithm for global optimization","volume-title":"Neural Computing and Applications","author":"Mirjalili","year":"2016"},{"key":"2025041407274831700_bib45","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey Wolf optimizer","volume-title":"Advances in Engineering Software","author":"Mirjalili","year":"2014"},{"key":"2025041407274831700_bib46","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.asoc.2018.02.027","article-title":"Modelling and optimization of ultimate bearing capacity of strip footing near a slope by soft computing methods","volume":"66","author":"Moayedi","year":"2018","journal-title":"Applied Soft Computing"},{"key":"2025041407274831700_bib47","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/s00521-017-2990-z","article-title":"An artificial neural network approach for under-reamed piles subjected to uplift forces in dry sand","volume":"31","author":"Moayedi","year":"2019","journal-title":"Neural Computing & Applications"},{"key":"2025041407274831700_bib48","doi-asserted-by":"publisher","first-page":"7391","DOI":"10.1007\/s11227-019-02951-1","article-title":"A novel optimized approach for resource reservation in cloud computing using producer-consumer theory of microeconomics","volume":"75","author":"Mohammadi","year":"2019","journal-title":"Journal of Supercomputing"},{"key":"2025041407274831700_bib49","doi-asserted-by":"publisher","first-page":"Article 107955","DOI":"10.1016\/j.asoc.2021.107955","article-title":"An entropy minimization based multilevel colour thresholding technique for analysis of breast thermograms using equilibrium slime mould algorithm","volume":"113","author":"Naik","year":"2021","journal-title":"Applied Soft Computing"},{"key":"2025041407274831700_bib50","doi-asserted-by":"publisher","first-page":"4524","DOI":"10.1016\/j.jksuci.2020.10.030","article-title":"Normalized square difference based multilevel thresholding technique for multispectral images using leader slime mould algorithm","volume":"34","author":"Naik","year":"2022","journal-title":"Journal of King Saud University-Computer and Information Sciences"},{"key":"2025041407274831700_bib51","doi-asserted-by":"publisher","first-page":"2375","DOI":"10.1093\/jcde\/qwac111","article-title":"Directional crossover slime mould algorithm with adaptive L\u00e9vy diversity for the optimal design of real-world problems","volume":"9","author":"Qi","year":"2022","journal-title":"Journal of Computational Design and Engineering"},{"key":"2025041407274831700_bib52","doi-asserted-by":"publisher","first-page":"110023","DOI":"10.1016\/j.enbuild.2020.110023","article-title":"Nature-inspired hybrid techniques of IWO, DA, ES, GA, and ICA, validated through a k-fold validation process predicting monthly natural gas consumption","volume":"217","author":"Qiao","year":"2020","journal-title":"Energy and Buildings"},{"key":"2025041407274831700_bib53","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1504\/ijahuc.2022.120947","article-title":"Behaviour-based grey wolf optimiser for a wireless sensor network deployment problem","volume":"39","author":"Qiao","year":"2022","journal-title":"International Journal of Ad Hoc and Ubiquitous Computing"},{"key":"2025041407274831700_bib54","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2007.4424748","article-title":"Quasi-oppositional differential evolution","author":"Rahnamayan","year":"2007","journal-title":"2007 IEEE Congress on Evolutionary Computation"},{"key":"2025041407274831700_bib55","doi-asserted-by":"publisher","first-page":"3765","DOI":"10.3390\/math10203765","article-title":"A modified group teaching optimization algorithm for solving constrained engineering optimization problems","volume":"10","author":"Rao","year":"2022","journal-title":"Mathematics"},{"key":"2025041407274831700_bib56","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","article-title":"Teaching\u2013learning-based optimization: A novel method for constrained mechanical design optimization problems","volume":"43","author":"Rao","year":"2011","journal-title":"Computer-Aided Design"},{"key":"2025041407274831700_bib57","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","article-title":"GSA: A gravitational search algorithm","volume":"179","author":"Rashedi","year":"2009","journal-title":"Information Sciences"},{"key":"2025041407274831700_bib58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2014.07.025","article-title":"Stochastic fractal search: a powerful metaheuristic algorithm","volume-title":"Knowledge-Based Systems","author":"Salimi","year":"2015"},{"key":"2025041407274831700_bib59","doi-asserted-by":"publisher","DOI":"10.1109\/CEC48606.2020.9185577","article-title":"Improved multi-operator differential evolution algorithm for solving unconstrained problems","author":"Sallam","year":"2020","journal-title":"2020 IEEE Congress on Evolutionary Computation (CEC)"},{"key":"2025041407274831700_bib60","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-2948-9_41","article-title":"A novel cosine swarm algorithm for solving optimization problems","volume-title":"Proceedings of 7th International Conference on Harmony Search, Soft Computing and Applications","author":"Sarangi","year":"2022"},{"key":"2025041407274831700_bib61","doi-asserted-by":"publisher","first-page":"2389","DOI":"10.1007\/s00366-020-00951-x","article-title":"A smart metaheuristic algorithm for solving engineering problems","volume":"37","author":"Sattar","year":"2021","journal-title":"Engineering with Computers"},{"key":"2025041407274831700_bib62","doi-asserted-by":"publisher","first-page":"104712","DOI":"10.1016\/j.compbiomed.2021.104712","article-title":"A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization","volume":"136","author":"Sayed","year":"2021","journal-title":"Computers in Biology and Medicine"},{"key":"2025041407274831700_bib63","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1016\/j.asoc.2018.07.033","article-title":"Farmland fertility: A new metaheuristic algorithm for solving continuous optimization problems","volume":"71","author":"Shayanfar","year":"2018","journal-title":"Applied Soft Computing"},{"key":"2025041407274831700_bib65","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1093\/jcde\/qwac112","article-title":"A horizontal and vertical crossover cuckoo search: Optimizing performance for the engineering problems","volume":"10","author":"Su","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2025041407274831700_bib66","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2013.6557555","article-title":"Success-history based parameter adaptation for Differential Evolution","author":"Tanabe","year":"2013","journal-title":"2013 IEEE Congress on Evolutionary Computation"},{"key":"2025041407274831700_bib67","doi-asserted-by":"publisher","first-page":"104968","DOI":"10.1016\/j.compbiomed.2021.104968","article-title":"Breast cancer prediction using a hybrid method based on Butterfly Optimization Algorithm and Ant Lion Optimizer","volume":"139","author":"Thawkar","year":"2021","journal-title":"Computers in Biology and Medicine"},{"key":"2025041407274831700_bib68","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1016\/j.ejor.2020.05.018","article-title":"Fuzzy self-tuning differential evolution for optimal product line design","volume":"287","author":"Tsafarakis","year":"2020","journal-title":"European Journal of Operational Research"},{"key":"2025041407274831700_bib70","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1007\/978-3-540-92910-9_24","article-title":"Genetic programming\u2014Introduction, applications, theory and Open issues","volume-title":"Handbook of Natural Computing","author":"Vanneschi","year":"2012"},{"key":"2025041407274831700_bib71","doi-asserted-by":"publisher","first-page":"Glasgow, UK","DOI":"10.1109\/CEC48606.2020.9185633","article-title":"DISH-XX solving CEC2020 single objective bound constrained numerical optimization benchmark","volume-title":"2020 IEEE Congress on Evolutionary Computation (CEC)","author":"Viktorin","year":"2020"},{"key":"2025041407274831700_bib72","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.1007\/s00521-015-1923-y","article-title":"Monarch butterfly optimization","volume-title":"Neural Computing and Applications","author":"Wang","year":"2019"},{"key":"2025041407274831700_bib73","doi-asserted-by":"publisher","first-page":"Article 105946","DOI":"10.1016\/j.asoc.2019.105946","article-title":"Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis","volume":"88","author":"Wang","year":"2020","journal-title":"Applied Soft Computing"},{"key":"2025041407274831700_bib74","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.neucom.2017.04.060","article-title":"Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses","volume":"267","author":"Wang","year":"2017","journal-title":"Neurocomputing"},{"key":"2025041407274831700_bib75","doi-asserted-by":"publisher","first-page":"2147","DOI":"10.1093\/jcde\/qwad062","article-title":"A modified smell agent optimization for global optimization and industrial engineering design problems","volume":"10","author":"Wang","year":"2023","journal-title":"Journal of Computational Design and Engineering"},{"key":"2025041407274831700_bib76","doi-asserted-by":"publisher","first-page":"7922","DOI":"10.1007\/s10489-021-02776-7","article-title":"Rank-driven salp swarm algorithm with orthogonal opposition-based learning for global optimization","volume":"52","author":"Wang","year":"2022","journal-title":"Applied Intelligence"},{"key":"2025041407274831700_bib77","doi-asserted-by":"publisher","first-page":"8742","DOI":"10.1016\/j.egyr.2021.11.138","article-title":"Optimal reactive power dispatch using an improved slime mould algorithm","volume":"7","author":"Wei","year":"2021","journal-title":"Energy Reports"},{"key":"2025041407274831700_bib78","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.3390\/e24091205","article-title":"An enhanced differential evolution algorithm with Bernstein operator and refracted oppositional-mutual learning strategy","volume":"24","author":"Wu","year":"2022","journal-title":"Entropy"},{"key":"2025041407274831700_bib79","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.3390\/e24091205","article-title":"An enhanced differential evolution algorithm with Bernstein operator and refracted oppositional-mutual learning strategy","volume":"24","author":"Wu","year":"2022","journal-title":"Entropy"},{"key":"2025041407274831700_bib80","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","article-title":"Evolutionary programming made faster","volume":"3","author":"Xin","year":"1999","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2025041407274831700_bib81","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1007\/s42235-022-00297-8","article-title":"Boosting whale optimizer with quasi-oppositional learning and gaussian barebone for feature selection and COVID-19 image segmentation","volume":"20","author":"Xing","year":"2023","journal-title":"Journal of Bionic Engineering"},{"key":"2025041407274831700_bib82","doi-asserted-by":"publisher","first-page":"7305","DOI":"10.1007\/s11227-022-04959-6","article-title":"Dung beetle optimizer: A new meta-heuristic algorithm for global optimization","volume":"79","author":"Xue","year":"2022","journal-title":"Journal of Supercomputing"},{"key":"2025041407274831700_bib83","doi-asserted-by":"publisher","first-page":"119041","DOI":"10.1016\/j.eswa.2022.119041","article-title":"An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems","volume":"213","author":"Yang","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"2025041407274831700_bib84","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s00521-013-1367-1","article-title":"Cuckoo search: Recent advances and applications","volume":"24","author":"Yang","year":"2014","journal-title":"Neural Computing and Applications"},{"key":"2025041407274831700_bib85","doi-asserted-by":"publisher","first-page":"114864","DOI":"10.1016\/j.eswa.2021.114864","article-title":"Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts","volume":"177","author":"Yang","year":"2021","journal-title":"Expert Systems with Applications"},{"key":"2025041407274831700_bib86","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s10462-021-10042-y","article-title":"A survey on evolutionary computation for complex continuous optimization","volume":"55","author":"Zhan","year":"2022","journal-title":"Artificial Intelligence Review"},{"key":"2025041407274831700_bib87","doi-asserted-by":"publisher","first-page":"1502988","DOI":"10.1155\/2022\/1502988","article-title":"Porcellio scaber algorithm with t-distributed elite mutation for Global optimization","volume-title":"Scientific Programming","author":"Zhang","year":"2022"},{"key":"2025041407274831700_bib88","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","article-title":"JADE: Adaptive differential evolution with optional external archive","volume":"13","author":"Zhang","year":"2009","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"2025041407274831700_bib89","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1093\/jcde\/qwae035","article-title":"A novel hippo swarm optimization: For solving high-dimensional problems and engineering design problems","volume":"11","author":"Zhou","year":"2024","journal-title":"Journal of Computational Design and Engineering"}],"container-title":["Journal of Computational Design and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jcde\/advance-article-pdf\/doi\/10.1093\/jcde\/qwae089\/59835837\/qwae089.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/6\/36\/61212557\/qwae089.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcde\/article-pdf\/11\/6\/36\/61212557\/qwae089.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T07:28:12Z","timestamp":1744615692000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jcde\/article\/11\/6\/36\/7825871"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,17]]},"references-count":87,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,11,8]]}},"URL":"https:\/\/doi.org\/10.1093\/jcde\/qwae089","relation":{},"ISSN":["2288-5048"],"issn-type":[{"type":"electronic","value":"2288-5048"}],"subject":[],"published-other":{"date-parts":[[2024,12]]},"published":{"date-parts":[[2024,10,17]]}}}