{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T19:59:13Z","timestamp":1776196753903,"version":"3.50.1"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003459","name":"Guizhou University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003459","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62466010"],"award-info":[{"award-number":["62466010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104608","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T14:09:40Z","timestamp":1774620580000},"page":"104608","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Multi-objective differential evolution algorithm based on partial reinforcement learning intelligence for engineering design problems and physics-informed neural networks"],"prefix":"10.1016","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4518-1429","authenticated-orcid":false,"given":"Jianqiang","family":"Yang","sequence":"first","affiliation":[]},{"given":"Fu","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Changgen","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Yuling","family":"Chen","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104608_b1","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution \u2013 A simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Global Optim."},{"key":"10.1016\/j.aei.2026.104608_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2023.110977","article-title":"Multi-objective optimal power flow of thermal-wind-solar power system using an adaptive geometry estimation based multi-objective differential evolution","volume":"149","author":"Huy","year":"2023","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.aei.2026.104608_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102895","article-title":"Mixed integer programming and multi-objective enhanced differential evolution algorithm for human\u2013robot responsive collaborative disassembly in remanufacturing system","volume":"62","author":"Zhang","year":"2024","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.104893","article-title":"Multi-threshold image segmentation based on an improved differential evolution: case study of thyroid papillary carcinoma","volume":"85","author":"Chen","year":"2023","journal-title":"Biomed. Signal Process. Contr."},{"issue":"10","key":"10.1016\/j.aei.2026.104608_b5","doi-asserted-by":"crossref","first-page":"14710","DOI":"10.1109\/TITS.2024.3394857","article-title":"EPQ-GAN: Evolutionary perceptual quality assessment generative adversarial network for image dehazing","volume":"25","author":"Ashwini","year":"2024","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.aei.2026.104608_b6","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.jmsy.2024.11.014","article-title":"Material removal rate optimization with bayesian optimized differential evolution based on deep learning in robotic polishing","volume":"78","author":"Wang","year":"2025","journal-title":"J. Manuf. Syst."},{"issue":"2","key":"10.1016\/j.aei.2026.104608_b7","doi-asserted-by":"crossref","first-page":"3756","DOI":"10.1109\/TTE.2023.3309332","article-title":"Manufacturing-based design methodology of permanent magnet machines considering practical slot-filling factor","volume":"10","author":"Jun Lee","year":"2024","journal-title":"IEEE Trans. Transp. Electrific."},{"key":"10.1016\/j.aei.2026.104608_b8","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.knosys.2012.10.003","article-title":"Differential evolution trained kernel principal component WNN and kernel binary quantile regression: Application to banking","volume":"39","author":"Reddy","year":"2013","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"10.1016\/j.aei.2026.104608_b9","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TEVC.2021.3087802","article-title":"Novel random key encoding schemes for the differential evolution of permutation problems","volume":"26","author":"Kr\u00f6mer","year":"2022","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.aei.2026.104608_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111262","article-title":"Improved differential evolution algorithm based convolutional neural network for emotional analysis of music data","volume":"153","author":"Li","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.aei.2026.104608_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108560","article-title":"A differential evolution framework based on the fluid model for feature selection","volume":"133","author":"Li","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"10","key":"10.1016\/j.aei.2026.104608_b12","doi-asserted-by":"crossref","first-page":"6676","DOI":"10.1109\/TCYB.2022.3213236","article-title":"Differential evolution with duplication analysis for feature selection in classification","volume":"53","author":"Wang","year":"2022","journal-title":"IEEE Trans. Cybern."},{"issue":"3","key":"10.1016\/j.aei.2026.104608_b13","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1109\/TGCN.2021.3061789","article-title":"Multi-energy scheduling of an industrial integrated energy system by reinforcement learning-based differential evolution","volume":"5","author":"Xu","year":"2021","journal-title":"IEEE Trans. Green Commun. Netw."},{"key":"10.1016\/j.aei.2026.104608_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.apm.2025.115979","article-title":"Hybrid chaos game and grey wolf optimization algorithms for UAV path planning","volume":"142","author":"Yang","year":"2025","journal-title":"Appl. Math. Model"},{"key":"10.1016\/j.aei.2026.104608_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102740","article-title":"Knowledge-assisted differential evolution based non-contact voltage measurement for multiconductor systems in smart grid","volume":"62","author":"Li","year":"2024","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103959","article-title":"A hybrid proximal policy optimization and particle swarm algorithm for highway alignment optimization","volume":"69","author":"Pu","year":"2026","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103598","article-title":"Urban feature simulation and optimization of points-of-interest networks based on coupled generative adversarial networks and genetic algorithm","volume":"68","author":"Ji","year":"2025","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b18","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103657","article-title":"Towards large-scale cotton blending optimization: dual-pheromone crossover ant colony algorithm with expert heuristic cognition","volume":"68","author":"Wang","year":"2025","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103941","article-title":"Human-intelligent trajectory optimization for robotic manipulators with hybrid PSO-PS algorithm","volume":"69","author":"Pe\u00f1acoba Yag\u00fce","year":"2026","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2026.104608_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103295","article-title":"A skill vector-based multi-task optimization algorithm for achieving objectives of multiple users in cloud manufacturing","volume":"65","author":"Jiang","year":"2025","journal-title":"Adv. Eng. Inform."},{"issue":"6","key":"10.1016\/j.aei.2026.104608_b21","doi-asserted-by":"crossref","first-page":"1794","DOI":"10.1109\/TEVC.2022.3232776","article-title":"Learning-aided evolution for optimization","volume":"27","author":"Zhan","year":"2023","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"10.1016\/j.aei.2026.104608_b22","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/TEVC.2023.3278132","article-title":"Knowledge learning for evolutionary computation","volume":"29","author":"Jiang","year":"2025","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"10.1016\/j.aei.2026.104608_b23","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1109\/TEVC.2021.3131236","article-title":"A meta-knowledge transfer-based differential evolution for multitask optimization","volume":"26","author":"Li","year":"2022","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"10.1016\/j.aei.2026.104608_b24","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.1007\/s40747-023-01243-9","article-title":"Dynamic multi-strategy integrated differential evolution algorithm based on reinforcement learning for optimization problems","volume":"10","author":"Yang","year":"2024","journal-title":"Complex Intell. Syst."},{"issue":"10","key":"10.1016\/j.aei.2026.104608_b25","doi-asserted-by":"crossref","first-page":"4719","DOI":"10.1109\/TNNLS.2017.2772870","article-title":"Reinforcement learning-based differential evolution with cooperative coevolution for a compensatory neuro-fuzzy controller","volume":"29","author":"Chen","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.aei.2026.104608_b26","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.swevo.2019.06.010","article-title":"Differential evolution based on reinforcement learning with fitness ranking for solving multimodal multiobjective problems","volume":"49","author":"Li","year":"2019","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.aei.2026.104608_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2022.101194","article-title":"Differential evolution with hybrid parameters and mutation strategies based on reinforcement learning","volume":"75","author":"Tan","year":"2022","journal-title":"Swarm Evol. Comput."},{"issue":"6","key":"10.1016\/j.aei.2026.104608_b28","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1109\/TETCI.2023.3251441","article-title":"Learning to learn evolutionary algorithm: A learnable differential evolution","volume":"7","author":"Liu","year":"2023","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"10.1016\/j.aei.2026.104608_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101568","article-title":"Differential evolution based on strategy adaptation and deep reinforcement learning for multimodal optimization problems","volume":"87","author":"Liao","year":"2024","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.aei.2026.104608_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122070","article-title":"Partial reinforcement optimizer: an evolutionary optimization algorithm","volume":"238","author":"Taheri","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.aei.2026.104608_b31","series-title":"Encyclopedia of the Sciences of Learning","first-page":"2929","article-title":"Schedules of reinforcement","author":"Lattal","year":"2012"},{"key":"10.1016\/j.aei.2026.104608_b32","series-title":"The ECPH Encyclopedia of Psychology","first-page":"1034","article-title":"Operant conditioning","author":"Guoli","year":"2024"},{"issue":"2","key":"10.1016\/j.aei.2026.104608_b33","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evolut. Comput."},{"key":"10.1016\/j.aei.2026.104608_b34","first-page":"743","article-title":"Multi-objective differential evolution - algorithm, convergence analysis, and applications","volume":"vol. 1","author":"Xue","year":"2005"},{"key":"10.1016\/j.aei.2026.104608_b35","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2023.110525","article-title":"A multi-objective chaos game optimization algorithm based on decomposition and random learning mechanisms for numerical optimization","volume":"144","author":"Yacoubi","year":"2023","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.aei.2026.104608_b36","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.eswa.2015.10.039","article-title":"Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization","volume":"47","author":"Mirjalili","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.aei.2026.104608_b37","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","article-title":"RIME: A physics-based optimization","volume":"532","author":"Su","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.aei.2026.104608_b38","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.enbuild.2016.04.027","article-title":"Multiobjective optimization using nondominated sorting genetic algorithm-II for allocation of energy conservation and renewable energy facilities in a campus","volume":"122","author":"Yang","year":"2016","journal-title":"Energy Build."},{"issue":"3","key":"10.1016\/j.aei.2026.104608_b39","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1137\/S1052623496307510","article-title":"Normal-boundary intersection: A new method for generating the Pareto surface in nonlinear multicriteria optimization problems","volume":"8","author":"Das","year":"1998","journal-title":"SIAM J. Optim."},{"key":"10.1016\/j.aei.2026.104608_b40","series-title":"Evolutionary Multi-Criterion Optimization","first-page":"862","article-title":"The hypervolume indicator revisited: On the design of Pareto-compliant indicators via weighted integration","author":"Zitzler","year":"2007"},{"issue":"2","key":"10.1016\/j.aei.2026.104608_b41","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/TEVC.2016.2587749","article-title":"Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes","volume":"21","author":"Ishibuchi","year":"2017","journal-title":"IEEE Trans. Evolut. Comput."},{"issue":"1","key":"10.1016\/j.aei.2026.104608_b42","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/TEVC.2015.2420112","article-title":"A new dominance relation-based evolutionary algorithm for many-objective optimization","volume":"20","author":"Yuan","year":"2016","journal-title":"IEEE Trans. Evolut. Comput."},{"key":"10.1016\/j.aei.2026.104608_b43","article-title":"A benchmark-suite of real-world constrained multi-objective optimization problems and some baseline results","volume":"67","author":"Kumar","year":"2021","journal-title":"Swarn Evol. Comput."},{"key":"10.1016\/j.aei.2026.104608_b44","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1007\/s10462-025-11129-6","article-title":"A novel reinforcement learning-based multi-operator differential evolution with cubic spline for the path planning problem","volume":"58","author":"Reda","year":"2025","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.aei.2026.104608_b45","article-title":"Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review","volume":"54","author":"Carrasco","year":"2020","journal-title":"Swarn Evol. Comput."},{"issue":"1","key":"10.1016\/j.aei.2026.104608_b46","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1162\/EVCO_a_00009","article-title":"HypE: An algorithm for fast hypervolume-based many-objective optimization","volume":"19","author":"Bader","year":"2011","journal-title":"Evol. Comput."},{"issue":"5","key":"10.1016\/j.aei.2026.104608_b47","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/0893-6080(89)90020-8","article-title":"Multilayer feedforward networks are universal approximators","volume":"2","author":"Hornik","year":"1989","journal-title":"Neural Netw."},{"issue":"7553","key":"10.1016\/j.aei.2026.104608_b48","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.aei.2026.104608_b49","series-title":"Proc. Fourteenth Int. Conf. Artif. Intell. Stat.","first-page":"315","article-title":"Deep sparse rectifier neural networks","volume":"vol. 15","author":"Glorot","year":"2011"},{"key":"10.1016\/j.aei.2026.104608_b50","series-title":"On loss functions for deep neural networks in classification","author":"Janocha","year":"2017"},{"key":"10.1016\/j.aei.2026.104608_b51","series-title":"An overview of gradient descent optimization algorithms","author":"Ruder","year":"2016"},{"key":"10.1016\/j.aei.2026.104608_b52","series-title":"ICML 2023 Workshop Proceedings","article-title":"Multi-objective PSO-PINN","author":"Davi","year":"2023"},{"key":"10.1016\/j.aei.2026.104608_b53","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2025.117303","article-title":"Multi-objective plant root growth optimization algorithm for engineering design problems and UAV path planning","volume":"201","author":"Yang","year":"2025","journal-title":"Chaos, Solitons Fractals"},{"issue":"2","key":"10.1016\/j.aei.2026.104608_b54","first-page":"404","article-title":"An efficient Differential Evolution based algorithm for solving multi-objective optimization problems","volume":"217","author":"Ali","year":"2012","journal-title":"European J. Oper. Res."},{"issue":"4","key":"10.1016\/j.aei.2026.104608_b55","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","article-title":"An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: Solving problems with box constraints","volume":"18","author":"Deb","year":"2014","journal-title":"IEEE Trans. Evol. Comput."}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003009?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003009?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T19:06:39Z","timestamp":1776193599000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626003009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":55,"alternative-id":["S1474034626003009"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104608","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-objective differential evolution algorithm based on partial reinforcement learning intelligence for engineering design problems and physics-informed neural networks","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104608","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"104608"}}