{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T11:28:26Z","timestamp":1762514906929,"version":"build-2065373602"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"The Postdoctoral Program at station of Gansu Province under Grant","award":["24JRRA217"],"award-info":[{"award-number":["24JRRA217"]}]},{"name":"The Young Doctors Program of Gansu Province under Grant","award":["2024QB-033"],"award-info":[{"award-number":["2024QB-033"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s13042-025-02768-w","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T05:19:09Z","timestamp":1753679949000},"page":"9535-9553","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Constrained multimodal multi-objective optimization based on cooperative evolution and neural network"],"prefix":"10.1007","volume":"16","author":[{"given":"Jie","family":"Cao","sequence":"first","affiliation":[]},{"given":"Yiyuan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jianlin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zuohan","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"key":"2768_CR1","doi-asserted-by":"publisher","first-page":"2027","DOI":"10.1109\/TSC.2023.3341842","volume":"17","author":"Z Xiao","year":"2024","unstructured":"Xiao Z, Qiu Q, Li L, Feng Y, Lin Q, Ming Z (2024) An efficient service-aware virtual machine scheduling approach based on multi-objective evolutionary algorithm. IEEE Trans Serv Comput 17:2027\u20132040. https:\/\/doi.org\/10.1109\/TSC.2023.3341842","journal-title":"IEEE Trans Serv Comput"},{"key":"2768_CR2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3392749","author":"L Li","year":"2024","unstructured":"Li L, Zhang Y, Lin Q, Ming Z, Coello CAC, Leung VCM (2024) Superpixel segmentation based evolutionary multitasking algorithm for feature selection of hyperspectral images. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2024.3392749","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR3","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1109\/TCE.2024.3376930","volume":"70","author":"L Li","year":"2024","unstructured":"Li L, Qiu Q, Xiao Z, Lin Q, Gu J, Ming Z (2024) A two-stage hybrid multi-objective optimization evolutionary algorithm for computing offloading in sustainable edge computing. IEEE Trans Consum Electron 70:735\u2013746. https:\/\/doi.org\/10.1109\/TCE.2024.3376930","journal-title":"IEEE Trans Consum Electron"},{"key":"2768_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101209","volume":"76","author":"F Ming","year":"2023","unstructured":"Ming F, Gong W, Yang Y, Liao Z (2023) Constrained multimodal multi-objective optimization: Test problem construction and algorithm design. Swarm Evol Comput 76:101209. https:\/\/doi.org\/10.1016\/j.swevo.2022.101209","journal-title":"Swarm Evol Comput"},{"key":"2768_CR5","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1109\/TEVC.2022.3194253","volume":"27","author":"J Liang","year":"2023","unstructured":"Liang J, Lin H, Yue C, Yu K, Guo Y, Qiao K (2023) Multiobjective differential evolution with speciation for constrained multimodal multiobjective optimization. IEEE Trans Evol Comput 27:1115\u20131129. https:\/\/doi.org\/10.1109\/TEVC.2022.3194253","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR6","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1007\/s00607-018-00693-1","volume":"101","author":"TE Babaee","year":"2019","unstructured":"Babaee TE, Alireza G, Milad H, Kumar SA, Tao H (2019) Multi-objective multi-mode resource constrained project scheduling problem using pareto-based algorithms. Computing 101:547\u2013570. https:\/\/doi.org\/10.1007\/s00607-018-00693-1","journal-title":"Computing"},{"key":"2768_CR7","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/JAS.2023.123792","volume":"11","author":"F Ming","year":"2024","unstructured":"Ming F, Gong W, Jin Y (2024) Even search in a promising region for constrained multi-objective optimization. IEEE\/CAA J Autom Sin 11:474\u2013486. https:\/\/doi.org\/10.1109\/JAS.2023.123792","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"2768_CR8","doi-asserted-by":"publisher","first-page":"1458","DOI":"10.1109\/JAS.2024.124377","volume":"11","author":"J Liang","year":"2024","unstructured":"Liang J, Lin H, Yue C, Suganthan PN, Wang Y (2024) Multiobjective differential evolution for higher-dimensional multimodal multiobjective optimization. IEEE\/CAA J Autom Sin 11:1458\u20131475. https:\/\/doi.org\/10.1109\/JAS.2024.124377","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"2768_CR9","doi-asserted-by":"publisher","first-page":"3873","DOI":"10.1109\/TCYB.2022.3163759","volume":"53","author":"J Liang","year":"2023","unstructured":"Liang J, Qiao K, Yu K, Qu B, Yue C, Guo W, Wang L (2023) Utilizing the relationship between unconstrained and constrained pareto fronts for constrained multiobjective optimization. IEEE Trans Cybern 53:3873\u20133886. https:\/\/doi.org\/10.1109\/TCYB.2022.3163759","journal-title":"IEEE Trans Cybern"},{"key":"2768_CR10","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.26599\/TST.2023.9010123","volume":"29","author":"GT Zhang","year":"2024","unstructured":"Zhang GT, Du YH, Zhu XB, Liu XL (2024) Hybrid operator and strengthened diversity improving for multimodal multi-objective optimization. Tsinghua Sci Technol 29:1409\u20131421. https:\/\/doi.org\/10.26599\/TST.2023.9010123","journal-title":"Tsinghua Sci Technol"},{"key":"2768_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119591","volume":"648","author":"J Zhou","year":"2023","unstructured":"Zhou J, Zhang Y, Suganthan PN (2023) Dual population approximate constrained pareto front for constrained multiobjective optimization. Inf Sci 648:119591. https:\/\/doi.org\/10.1016\/j.ins.2023.119591","journal-title":"Inf Sci"},{"key":"2768_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3393921","author":"T Zheng","year":"2024","unstructured":"Zheng T, Liu J, Jin Y, Liu Y (2024) A multitask-assisted evolutionary algorithm for constrained multimodal multiobjective optimization. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2024.3393921","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR13","doi-asserted-by":"publisher","first-page":"7561","DOI":"10.1109\/TII.2022.3211853","volume":"19","author":"Q Yu","year":"2023","unstructured":"Yu Q, Yang C, Dai G, Peng L, Chen X (2023) Synchronous wireless sensor and sink placement method using dual-population co-evolutionary constrained multiobjective optimization algorithm. IEEE Trans Industr Inf 19:7561\u20137571. https:\/\/doi.org\/10.1109\/TII.2022.3211853","journal-title":"IEEE Trans Industr Inf"},{"key":"2768_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103655","volume":"126","author":"J Liu","year":"2021","unstructured":"Liu J, Li S, Xu C, Wu Z, Ao N, Frank CY (2021) Automatic and optimal rebar layout in reinforced concrete structure by decomposed optimization algorithms. Autom Constr 126:103655. https:\/\/doi.org\/10.1016\/j.autcon.2021.103655","journal-title":"Autom Constr"},{"key":"2768_CR15","doi-asserted-by":"publisher","first-page":"6286","DOI":"10.1109\/TNNLS.2021.3075205","volume":"33","author":"XF Liu","year":"2022","unstructured":"Liu XF, Zhan ZH, Zhang J (2022) Resource-aware distributed differential evolution for training expensive neural-network-based controller in power electronic circuit. IEEE Trans Neural Netw Learn Syst 33:6286\u20136296. https:\/\/doi.org\/10.1109\/TNNLS.2021.3075205","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2768_CR16","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/TEVC.2022.3155533","volume":"27","author":"J Liang","year":"2023","unstructured":"Liang J, Ban X, Yu K, Qu B, Qiao K, Yue C, Chen K, Tan KC (2023) A survey on evolutionary constrained multiobjective optimization. IEEE Trans Evol Comput 27:201\u2013221. https:\/\/doi.org\/10.1109\/TEVC.2022.3155533","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR17","doi-asserted-by":"publisher","first-page":"1376","DOI":"10.1109\/TSMC.2023.3324797","volume":"54","author":"J Zhou","year":"2024","unstructured":"Zhou J, Zhang Y, Wang J, Suganthan PN (2024) Localized constrained-domination principle for constrained multiobjective optimization. IEEE Trans Syst Man Cybern Syst 54:1376\u20131387. https:\/\/doi.org\/10.1109\/TSMC.2023.3324797","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"2768_CR18","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1109\/TEVC.2021.3066301","volume":"25","author":"M Ming","year":"2021","unstructured":"Ming M, Trivedi A, Wang R, Srinivasan D, Zhang T (2021) A dual-population-based evolutionary algorithm for constrained multiobjective optimization. IEEE Trans Evol Comput 25:739\u2013753. https:\/\/doi.org\/10.1109\/TEVC.2021.3066301","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR19","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1109\/JAS.2023.123336","volume":"10","author":"K Qiao","year":"2023","unstructured":"Qiao K, Liang J, Liu Z, Yu K, Yue C, Qu B (2023) Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization. IEEE\/CAA J Autom Sin 10:1951\u20131964. https:\/\/doi.org\/10.1109\/JAS.2023.123336","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"2768_CR20","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1109\/TETCI.2023.3236633","volume":"7","author":"K Qiao","year":"2023","unstructured":"Qiao K, Liang J, Yu K, Wang M, Qu B, Yue C, Guo Y (2023) A self-adaptive evolutionary multi-task based constrained multi-objective evolutionary algorithm. IEEE Trans Emerg Top Comput Intell 7:1098\u20131112. https:\/\/doi.org\/10.1109\/TETCI.2023.3236633","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"key":"2768_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101417","volume":"83","author":"T Zhou","year":"2023","unstructured":"Zhou T, He P, Niu B, Yue G, Wang H (2023) A novel competitive constrained dual-archive dual-stage evolutionary algorithm for constrained multiobjective optimization. Swarm Evol Comput 83:101417. https:\/\/doi.org\/10.1016\/j.swevo.2023.101417","journal-title":"Swarm Evol Comput"},{"key":"2768_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101402","volume":"83","author":"J Liang","year":"2023","unstructured":"Liang J, Zhang L, Yu K, Qu B, Shang F, Qiao K (2023) Interactive niching-based two-stage evolutionary algorithm for constrained multiobjective optimization. Swarm Evol Comput 83:101402. https:\/\/doi.org\/10.1016\/j.swevo.2023.101402","journal-title":"Swarm Evol Comput"},{"key":"2768_CR23","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/TEVC.2022.3202723","volume":"28","author":"K Zhang","year":"2024","unstructured":"Zhang K, Xu Z, Yen GG, Zhang L (2024) Two-stage multiobjective evolution strategy for constrained multiobjective optimization. IEEE Trans Evol Comput 28:17\u201331. https:\/\/doi.org\/10.1109\/TEVC.2022.3202723","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR24","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1109\/TCYB.2022.3186591","volume":"54","author":"F Li","year":"2024","unstructured":"Li F, Gao L, Shen W (2024) Surrogate-assisted multi-objective evolutionary optimization with pareto front model-based local search method. IEEE Trans Cybern 54:173\u2013186. https:\/\/doi.org\/10.1109\/TCYB.2022.3186591","journal-title":"IEEE Trans Cybern"},{"key":"2768_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2023.3281666","author":"K Qiao","year":"2023","unstructured":"Qiao K, Liang J, Yu K, Yue C, Lin H, Zhang D, Qu B (2023) Evolutionary constrained multiobjective optimization: Scalable high-dimensional constraint benchmarks and algorithm. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2023.3281666","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR26","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1109\/JAS.2023.123687","volume":"11","author":"F Ming","year":"2024","unstructured":"Ming F, Gong W, Wang L, Jin Y (2024) Constrained multi-objective optimization with deep reinforcement learning assisted operator selection. IEEE\/CAA J Autom Sin 11:919\u2013931. https:\/\/doi.org\/10.1109\/JAS.2023.123687","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"2768_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101253","volume":"77","author":"W Li","year":"2023","unstructured":"Li W, Zhang T, Wang R, Huang S, Liang J (2023) Multimodal multi-objective optimization: Comparative study of the state-of-the-art. Swarm Evol Comput 77:101253. https:\/\/doi.org\/10.1016\/j.swevo.2023.101253","journal-title":"Swarm Evol Comput"},{"key":"2768_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2024.130996","volume":"295","author":"LF Yin","year":"2024","unstructured":"Yin LF, Cai ZJ (2024) Multimodal multi-objective hierarchical distributed consensus method for multimodal multi-objective economic dispatch of hierarchical distributed power systems. Energy 295:130996. https:\/\/doi.org\/10.1016\/j.energy.2024.130996","journal-title":"Energy"},{"key":"2768_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.118990","volume":"639","author":"CC Yang","year":"2023","unstructured":"Yang CC, Wu TX, Ji JZ (2023) Two-stage species conservation for multimodal multi-objective optimization with local pareto sets. Inf Sci 639:118990. https:\/\/doi.org\/10.1016\/j.ins.2023.118990","journal-title":"Inf Sci"},{"key":"2768_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122042","volume":"238","author":"HZ Zhang","year":"2024","unstructured":"Zhang HZ, Huang Q, Ma L, Zhang ZY (2024) Sparrow search algorithm with adaptive t distribution for multi-objective low-carbon multimodal transportation planning problem with fuzzy demand and fuzzy time. Expert Syst Appl 238:122042. https:\/\/doi.org\/10.1016\/j.eswa.2023.122042","journal-title":"Expert Syst Appl"},{"key":"2768_CR31","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1109\/TEVC.2017.2754271","volume":"22","author":"C Yue","year":"2018","unstructured":"Yue C, Qu B, Liang J (2018) A multiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems. IEEE Trans Evol Comput 22:805\u2013817. https:\/\/doi.org\/10.1109\/TEVC.2017.2754271","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR32","doi-asserted-by":"publisher","unstructured":"Wang Y, Yang Z, Guo Y, Zhu J, Zhu X (2019) A novel multi-objective competitive swarm optimization algorithm for multi-modal multi objective problems. 2019 IEEE Congress on Evolutionary Computation (CEC), 271\u2013278. https:\/\/doi.org\/10.1109\/CEC.2019.8790218","DOI":"10.1109\/CEC.2019.8790218"},{"key":"2768_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2021.100843","volume":"62","author":"G Li","year":"2021","unstructured":"Li G, Wang W, Zhang W, Wang Z, Tu H, You W (2021) Grid search based multi-population particle swarm optimization algorithm for multimodal multi-objective optimization. Swarm Evol Comput 62:100843. https:\/\/doi.org\/10.1016\/j.swevo.2021.100843","journal-title":"Swarm Evol Comput"},{"key":"2768_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2020.100788","volume":"60","author":"J Liang","year":"2021","unstructured":"Liang J, Qiao K, Yue C, Yu K, Qu B, Xu R, Li Z, Hu Y (2021) A clustering-based differential evolution algorithm for solving multimodal multi-objective optimization problems. Swarm Evol Comput 60:100788. https:\/\/doi.org\/10.1016\/j.swevo.2020.100788","journal-title":"Swarm Evol Comput"},{"key":"2768_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.108606","volume":"119","author":"Y Hu","year":"2022","unstructured":"Hu Y, Wang J, Liang J, Wang Y, Ashraf U, Yue C, Yu K (2022) A two-archive model based evolutionary algorithm for multimodal multi-objective optimization problems. Appl Soft Comput 119:108606. https:\/\/doi.org\/10.1016\/j.asoc.2022.108606","journal-title":"Appl Soft Comput"},{"key":"2768_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.108381","volume":"117","author":"B Qu","year":"2022","unstructured":"Qu B, Li G, Yan L, Liang J, Yue C, Yu K, Crisalle OD (2022) A grid-guided particle swarm optimizer for multimodal multi-objective problems. Appl Soft Comput 117:108381. https:\/\/doi.org\/10.1016\/j.asoc.2021.108381","journal-title":"Appl Soft Comput"},{"key":"2768_CR37","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1109\/TEVC.2019.2938557","volume":"24","author":"Y Liu","year":"2020","unstructured":"Liu Y, Ishibuchi H, Yen GG, Nojima Y, Masuyama N (2020) Handling imbalance between convergence and diversity in the decision space in evolutionary multimodal multiobjective optimization. IEEE Trans Evol Comput 24:551\u2013565. https:\/\/doi.org\/10.1109\/TEVC.2019.2938557","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR38","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1109\/TEVC.2021.3078441","volume":"25","author":"W Li","year":"2021","unstructured":"Li W, Zhang T, Wang R, Ishibuchi H (2021) Weighted indicator-based evolutionary algorithm for multimodal multiobjective optimization. IEEE Trans Evol Comput 25:1064\u20131078. https:\/\/doi.org\/10.1109\/TEVC.2021.3078441","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2024.101541","volume":"87","author":"F Ming","year":"2024","unstructured":"Ming F, Gong WY, Jin YC (2024) Growing neural gas network-based surrogate-assisted pareto set learning for multimodal multi-objective optimization. Swarm Evol Comput 87:101541. https:\/\/doi.org\/10.1016\/j.swevo.2024.101541","journal-title":"Swarm Evol Comput"},{"key":"2768_CR40","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.neunet.2022.03.021","volume":"151","author":"A Triche","year":"2022","unstructured":"Triche A, Maida AS, Kumar A (2022) Exploration in neo-hebbian reinforcement learning: computational approaches to the exploration\u2013exploitation balance with bio-inspired neural networks. Neural Netw 151:16\u201333. https:\/\/doi.org\/10.1016\/j.neunet.2022.03.021","journal-title":"Neural Netw"},{"key":"2768_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101273","volume":"78","author":"R Hong","year":"2023","unstructured":"Hong R, Yao F, Liao T, Xing L, Cai Z, Hou F (2023) Growing neural gas assisted evolutionary many-objective optimization for handling irregular pareto fronts. Swarm Evol Comput 78:101273. https:\/\/doi.org\/10.1016\/j.swevo.2023.101273","journal-title":"Swarm Evol Comput"},{"key":"2768_CR42","doi-asserted-by":"publisher","first-page":"2698","DOI":"10.1109\/TCYB.2020.3020630","volume":"52","author":"Q Liu","year":"2022","unstructured":"Liu Q, Jin Y, Heiderich M, Rodemann T, Yu G (2022) An adaptive reference vector-guided evolutionary algorithm using growing neural gas for many-objective optimization of irregular problems. IEEE Trans Cybern 52:2698\u20132711. https:\/\/doi.org\/10.1109\/TCYB.2020.3020630","journal-title":"IEEE Trans Cybern"},{"key":"2768_CR43","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1109\/TETCI.2023.3313412","volume":"8","author":"C Wang","year":"2024","unstructured":"Wang C, Huang H, Zhang X (2024) Growing neural gas network for offspring generation in evolutionary constrained multi-objective optimization. IEEE Trans Emerg Top Comput Intell 8:576\u2013590. https:\/\/doi.org\/10.1109\/TETCI.2023.3313412","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"key":"2768_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101162","volume":"75","author":"Q Gu","year":"2022","unstructured":"Gu Q, Bai J, Li X, Xiong N, Lu C (2022) A constrained multi-objective evolutionary algorithm based on decomposition with improved constrained dominance principle. Swarm Evol Comput 75:101162. https:\/\/doi.org\/10.1016\/j.swevo.2022.101162","journal-title":"Swarm Evol Comput"},{"key":"2768_CR45","doi-asserted-by":"publisher","first-page":"10163","DOI":"10.1109\/TCYB.2021.3056176","volume":"52","author":"ZZ Liu","year":"2022","unstructured":"Liu ZZ, Wang BC, Tang K (2022) Handling constrained multiobjective optimization problems via bidirectional coevolution. IEEE Trans Cybern 52:10163\u201310176. https:\/\/doi.org\/10.1109\/TCYB.2021.3056176","journal-title":"IEEE Trans Cybern"},{"key":"2768_CR46","doi-asserted-by":"publisher","first-page":"2954","DOI":"10.1109\/TSMC.2021.3061698","volume":"52","author":"K Yu","year":"2022","unstructured":"Yu K, Liang J, Qu B, Luo Y, Yue C (2022) Dynamic selection preference-assisted constrained multiobjective differential evolution. IEEE Trans Syst Man Cybern Syst 52:2954\u20132965. https:\/\/doi.org\/10.1109\/TSMC.2021.3061698","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"2768_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.127382","volume":"577","author":"L Yang","year":"2024","unstructured":"Yang L, Gong W, Li Q, Sun F, Xing M (2024) Multistability analysis of complex-valued recurrent neural networks with sine and cosine activation functions. Neurocomputing 577:127382. https:\/\/doi.org\/10.1016\/j.neucom.2024.127382","journal-title":"Neurocomputing"},{"key":"2768_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119370","volume":"645","author":"S Chen","year":"2023","unstructured":"Chen S, Ke M (2023) Multiattribute decision making method based on nonlinear programming model, cosine similarity measure, and novel score function of interval-valued intuitionistic fuzzy values. Inf Sci 645:119370. https:\/\/doi.org\/10.1016\/j.ins.2023.119370","journal-title":"Inf Sci"},{"key":"2768_CR49","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1109\/TEVC.2019.2896967","volume":"23","author":"Z Ma","year":"2019","unstructured":"Ma Z, Wang Y (2019) Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons. IEEE Trans Evol Comput 23:972\u2013986. https:\/\/doi.org\/10.1109\/TEVC.2019.2896967","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR50","doi-asserted-by":"publisher","first-page":"1544","DOI":"10.1109\/JAS.2023.123609","volume":"10","author":"W Li","year":"2023","unstructured":"Li W, Yao X, Li K, Wang R, Zhang T, Wang L (2023) Coevolutionary framework for generalized multimodal multi-objective optimization. IEEE\/CAA J Autom Sin 10:1544\u20131556. https:\/\/doi.org\/10.1109\/JAS.2023.123609","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"2768_CR51","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1016\/j.ins.2021.07.048","volume":"578","author":"R Jiao","year":"2021","unstructured":"Jiao R, Zeng S, Li C, Ong Y-S (2021) Two-type weight adjustments in moea\/d for highly constrained many-objective optimization. Inf Sci 578:592\u2013614. https:\/\/doi.org\/10.1016\/j.ins.2021.07.048","journal-title":"Inf Sci"},{"key":"2768_CR52","doi-asserted-by":"publisher","unstructured":"Liang JJ, Yue CT, Qu BY (2016) Multimodal multi-objective optimization: A preliminary study. 2016 IEEE Congress on Evolutionary Computation (CEC), 2454\u20132461. https:\/\/doi.org\/10.1109\/CEC.2016.7744093","DOI":"10.1109\/CEC.2016.7744093"},{"key":"2768_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2020.100759","volume":"60","author":"L Pan","year":"2021","unstructured":"Pan L, Xu W, Li L, He C, Cheng R (2021) Adaptive simulated binary crossover for rotated multi-objective optimization. Swarm Evol Comput 60:100759. https:\/\/doi.org\/10.1016\/j.swevo.2020.100759","journal-title":"Swarm Evol Comput"},{"issue":"2","key":"2768_CR54","first-page":"115","volume":"9","author":"K Deb","year":"1995","unstructured":"Deb K, Agrawal RB (1995) Simulated binary crossover for continuous search space. Complex Syst 9(2):115\u2013148","journal-title":"Complex Syst"},{"key":"2768_CR55","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","volume":"12","author":"Y Tian","year":"2017","unstructured":"Tian Y, Cheng R, Zhang X, Jin Y (2017) Platemo: A matlab platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput Intell Mag 12:73\u201387. https:\/\/doi.org\/10.1109\/MCI.2017.2742868","journal-title":"IEEE Comput Intell Mag"},{"key":"2768_CR56","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1109\/TEVC.2009.2021467","volume":"13","author":"A Zhou","year":"2009","unstructured":"Zhou A, Zhang Q, Jin Y (2009) Approximating the set of pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm. IEEE Trans Evol Comput 13:1167\u20131189. https:\/\/doi.org\/10.1109\/TEVC.2009.2021467","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR57","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1109\/TEVC.2003.810758","volume":"7","author":"E Zitzler","year":"2003","unstructured":"Zitzler E, Thiele L, Laumanns M, Fonseca CM, Fonseca VG (2003) Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans Evol Comput 7:117\u2013132. https:\/\/doi.org\/10.1109\/TEVC.2003.810758","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR58","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1109\/TEVC.2007.894202","volume":"12","author":"Q Zhang","year":"2008","unstructured":"Zhang Q, Zhou A, Jin Y (2008) Rm-meda: A regularity model-based multiobjective estimation of distribution algorithm. IEEE Trans Evol Comput 12:41\u201363. https:\/\/doi.org\/10.1109\/TEVC.2007.894202","journal-title":"IEEE Trans Evol Comput"},{"key":"2768_CR59","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2024.101541","volume":"87","author":"F Ming","year":"2024","unstructured":"Ming F, Gong W, Jin Y (2024) Growing neural gas network-based surrogate-assisted pareto set learning for multimodal multi-objective optimization. Swarm Evol Comput 87:101541. https:\/\/doi.org\/10.1016\/j.swevo.2024.101541","journal-title":"Swarm Evol Comput"},{"key":"2768_CR60","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1109\/TEVC.2019.2926151","volume":"24","author":"Y Liu","year":"2008","unstructured":"Liu Y, Ishibuchi H, Masuyama N, Nojima Y (2008) Adapting reference vectors and scalarizing functions by growing neural gas to handle irregular pareto fronts. IEEE Trans Evol Comput 24:439\u2013453. https:\/\/doi.org\/10.1109\/TEVC.2019.2926151","journal-title":"IEEE Trans Evol Comput"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02768-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-025-02768-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02768-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T11:23:26Z","timestamp":1762514606000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-025-02768-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,28]]},"references-count":60,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["2768"],"URL":"https:\/\/doi.org\/10.1007\/s13042-025-02768-w","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2025,7,28]]},"assertion":[{"value":"12 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 July 2025","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 Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}