{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T20:54:38Z","timestamp":1774904078208,"version":"3.50.1"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Industrial Engineering"],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1016\/j.cie.2025.111159","type":"journal-article","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T00:42:32Z","timestamp":1746751352000},"page":"111159","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"special_numbering":"C","title":["Intelligent Many-objective portfolio optimization using hybrid deep learning and evolutionary algorithm approach for advanced decision-making"],"prefix":"10.1016","volume":"205","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1227-2172","authenticated-orcid":false,"given":"Nikunj K.","family":"Joshi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jayesh M.","family":"Dhodiya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.cie.2025.111159_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109450","article-title":"Predictive multi-period multi-objective portfolio optimization based on higher order moments: Deep learning approach","volume":"183","author":"Abolmakarem","year":"2023","journal-title":"Computers & Industrial Engineering"},{"issue":"9","key":"10.1016\/j.cie.2025.111159_b2","doi-asserted-by":"crossref","first-page":"5641","DOI":"10.1007\/s00500-022-07646-z","article-title":"Non-dominated sorting genetic algorithm III with stochastic matrix-based population to solve multi-objective solid transportation problem","volume":"27","author":"Agnihotri","year":"2023","journal-title":"Soft Computing"},{"issue":"Special issue III","key":"10.1016\/j.cie.2025.111159_b3","first-page":"189","article-title":"Variants of genetic algorithm to solve multi-objective interval solid transportation problem","volume":"11","author":"Agnihotri","year":"2022","journal-title":"Palestine Journal of Mathematics"},{"issue":"3","key":"10.1016\/j.cie.2025.111159_b4","doi-asserted-by":"crossref","first-page":"52","DOI":"10.3390\/technologies9030052","article-title":"Effect of data scaling methods on machine learning algorithms and model performance","volume":"9","author":"Ahsan","year":"2021","journal-title":"Technologies"},{"key":"10.1016\/j.cie.2025.111159_b5","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.eswa.2017.10.056","article-title":"A polynomial goal programming model for portfolio optimization based on entropy and higher moments","volume":"94","author":"Aksarayl\u0131","year":"2018","journal-title":"Expert Systems with Applications"},{"issue":"2","key":"10.1016\/j.cie.2025.111159_b6","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/j.ejor.2015.01.025","article-title":"Multi-objective portfolio optimization considering the dependence structure of asset returns","volume":"244","author":"Babaei","year":"2015","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"10.1016\/j.cie.2025.111159_b7","article-title":"Multi-objective quasi oppositional Jaya algorithm to solve multi-objective solid travelling salesman problem with different aspiration level","volume":"10","author":"Bajaj","year":"2023","journal-title":"International Journal of Systems Science: Operations & Logistics"},{"key":"10.1016\/j.cie.2025.111159_b8","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.105843","article-title":"Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets","volume":"120","author":"Behera","year":"2023","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"10.1016\/j.cie.2025.111159_b9","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.dib.2016.12.044","article-title":"Stock market index data and indicators for day trading as a binary classification problem","volume":"10","author":"Bruni","year":"2017","journal-title":"Data in Brief"},{"key":"10.1016\/j.cie.2025.111159_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.najef.2022.101818","article-title":"A novel two-stage method for well-diversified portfolio construction based on stock return prediction using machine learning","volume":"63","author":"Chen","year":"2022","journal-title":"The North American Journal of Economics and Finance"},{"key":"10.1016\/j.cie.2025.111159_b11","series-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014"},{"key":"10.1016\/j.cie.2025.111159_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107519","article-title":"Multi-period uncertain portfolio optimization model with minimum transaction lots and dynamic risk preference","volume":"109","author":"Dai","year":"2021","journal-title":"Applied Soft Computing"},{"issue":"4","key":"10.1016\/j.cie.2025.111159_b13","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":"2013","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"2","key":"10.1016\/j.cie.2025.111159_b14","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 Transactions on Evolutionary Computation"},{"key":"10.1016\/j.cie.2025.111159_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2022.105626","article-title":"Forecasting stock market for an efficient portfolio by combining XGBoost and Hilbert\u2013Huang transform","volume":"118","author":"Dezhkam","year":"2023","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"7","key":"10.1016\/j.cie.2025.111159_b16","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1073\/pnas.1710231115","article-title":"Iterative near-term ecological forecasting: Needs, opportunities, and challenges","volume":"115","author":"Dietze","year":"2018","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"10.1016\/j.cie.2025.111159_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117005","article-title":"Mean\u2013variance portfolio optimization with deep learning based-forecasts for cointegrated stocks","volume":"201","author":"Du","year":"2022","journal-title":"Expert Systems with Applications"},{"issue":"11","key":"10.1016\/j.cie.2025.111159_b18","first-page":"14072","article-title":"Applying a GA kernel on optimizing technical analysis rules for stock picking and portfolio composition","volume":"38","author":"Gorgulho","year":"2011","journal-title":"Expert Systems with Applications"},{"issue":"13","key":"10.1016\/j.cie.2025.111159_b19","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1016\/j.ifacol.2021.10.501","article-title":"Effective solving portfolio optimization problems by means of a multi-period diversification model","volume":"54","author":"Guliashki","year":"2021","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.cie.2025.111159_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.114135","article-title":"Multi-period portfolio optimization using coherent fuzzy numbers in a credibilistic environment","volume":"167","author":"Gupta","year":"2021","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.cie.2025.111159_b21","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2019.105781","article-title":"A polynomial goal programming approach for intuitionistic fuzzy portfolio optimization using entropy and higher moments","volume":"85","author":"Gupta","year":"2019","journal-title":"Applied Soft Computing"},{"issue":"3","key":"10.1016\/j.cie.2025.111159_b22","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1111\/0022-1082.00247","article-title":"Conditional skewness in asset pricing tests","volume":"55","author":"Harvey","year":"2000","journal-title":"The Journal of Finance"},{"key":"10.1016\/j.cie.2025.111159_b23","doi-asserted-by":"crossref","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","author":"Hochreiter","year":"1997","journal-title":"Neural Computation MIT-Press"},{"issue":"5","key":"10.1016\/j.cie.2025.111159_b24","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/S0927-5398(03)00005-7","article-title":"Testing for differences in the tails of stock-market returns","volume":"10","author":"Jondeau","year":"2003","journal-title":"Journal of Empirical Finance"},{"issue":"5","key":"10.1016\/j.cie.2025.111159_b25","doi-asserted-by":"crossref","first-page":"5311","DOI":"10.1016\/j.eswa.2010.10.027","article-title":"Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul stock exchange","volume":"38","author":"Kara","year":"2011","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.cie.2025.111159_b26","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"issue":"11","key":"10.1016\/j.cie.2025.111159_b27","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun","year":"1998","journal-title":"Proceedings of the IEEE"},{"issue":"10","key":"10.1016\/j.cie.2025.111159_b28","doi-asserted-by":"crossref","first-page":"4741","DOI":"10.1007\/s00521-020-05532-z","article-title":"A CNN-BiLSTM-AM method for stock price prediction","volume":"33","author":"Lu","year":"2021","journal-title":"Neural Computing and Applications"},{"key":"10.1016\/j.cie.2025.111159_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109023","article-title":"A novel prediction based portfolio optimization model using deep learning","volume":"177","author":"Ma","year":"2023","journal-title":"Computers & Industrial Engineering"},{"issue":"2","key":"10.1016\/j.cie.2025.111159_b30","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1111\/j.1540-6261.1991.tb02669.x","article-title":"Foundations of portfolio theory","volume":"46","author":"Markowitz","year":"1991","journal-title":"The Journal of Finance"},{"issue":"1","key":"10.1016\/j.cie.2025.111159_b31","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1111\/j.1368-423X.2008.00230.x","article-title":"Exact formulas for the Hodrick-Prescott filter","volume":"11","author":"McElroy","year":"2008","journal-title":"The Econometrics Journal"},{"key":"10.1016\/j.cie.2025.111159_b32","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/j.asoc.2017.09.025","article-title":"Multi-objective heuristic algorithms for practical portfolio optimization and rebalancing with transaction cost","volume":"67","author":"Meghwani","year":"2018","journal-title":"Applied Soft Computing"},{"issue":"3","key":"10.1016\/j.cie.2025.111159_b33","doi-asserted-by":"crossref","first-page":"332","DOI":"10.3390\/e22030332","article-title":"An entropy-based approach to portfolio optimization","volume":"22","author":"Mercurio","year":"2020","journal-title":"Entropy"},{"key":"10.1016\/j.cie.2025.111159_b34","doi-asserted-by":"crossref","first-page":"127","DOI":"10.19041\/APSTRACT\/2017\/1-2\/16","article-title":"Note on simple and logarithmic return","volume":"11","author":"Panna","year":"2017","journal-title":"APSTRACT: Applied Studies in Agribusiness and Commerce"},{"issue":"4","key":"10.1016\/j.cie.2025.111159_b35","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1016\/S0893-6080(98)00010-0","article-title":"Automatic early stopping using cross validation: quantifying the criteria","volume":"11","author":"Prechelt","year":"1998","journal-title":"Neural Networks"},{"key":"10.1016\/j.cie.2025.111159_b36","doi-asserted-by":"crossref","unstructured":"Premaratne, G., & Bera, A. K. (2000). Modeling asymmetry and excess kurtosis in stock return data: Illinois research & reference working paper no. 00-123, URL: https:\/\/ssrn.com\/abstract=259009.","DOI":"10.2139\/ssrn.259009"},{"issue":"8","key":"10.1016\/j.cie.2025.111159_b37","doi-asserted-by":"crossref","first-page":"2760","DOI":"10.1007\/s40815-020-00928-4","article-title":"Fuzzy multi-objective particle swarm optimization solving the three-objective portfolio optimization problem","volume":"22","author":"Rangel-Gonz\u00e1lez","year":"2020","journal-title":"International Journal of Fuzzy Systems"},{"issue":"4","key":"10.1016\/j.cie.2025.111159_b38","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1007\/s00158-019-02272-0","article-title":"Many-objective differential evolution optimization based on reference points: NSDE-R","volume":"60","author":"Reddy","year":"2019","journal-title":"Structural and Multidisciplinary Optimization"},{"issue":"24","key":"10.1016\/j.cie.2025.111159_b39","first-page":"171","article-title":"A survey of forecast error measures","volume":"24","author":"Shcherbakov","year":"2013","journal-title":"World Applied Sciences Journal"},{"key":"10.1016\/j.cie.2025.111159_b40","doi-asserted-by":"crossref","first-page":"157","DOI":"10.14208\/BF03353829","article-title":"A higher moment downside framework for conditional and unconditional CAPM in the Russian stock market","volume":"1","author":"Teplova","year":"2011","journal-title":"Eurasian Economic Review"},{"issue":"4","key":"10.1016\/j.cie.2025.111159_b41","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1080\/10255810390245627","article-title":"Neural networks as a decision maker for stock trading: a technical analysis approach","volume":"5","author":"Thawornwong","year":"2003","journal-title":"International Journal of Smart Engineering System Design"},{"issue":"2","key":"10.1016\/j.cie.2025.111159_b42","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1504\/IJMOR.2024.137054","article-title":"Aspiration level-based non-dominated sorting genetic algorithm-II and III for multi-objective shortest path problem in a trapezoidal environment","volume":"27","author":"Todkar","year":"2024","journal-title":"International Journal of Mathematics in Operational Research"},{"key":"10.1016\/j.cie.2025.111159_b43","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.cie.2025.111159_b44","series-title":"New concepts in technical trading systems","author":"Wilder","year":"1978"},{"issue":"3","key":"10.1016\/j.cie.2025.111159_b45","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1007\/s00530-021-00758-w","article-title":"A graph-based CNN-LSTM stock price prediction algorithm with leading indicators","volume":"29","author":"Wu","year":"2023","journal-title":"Multimedia Systems"},{"key":"10.1016\/j.cie.2025.111159_b46","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.neucom.2020.12.022","article-title":"Multiple populations co-evolutionary particle swarm optimization for multi-objective cardinality constrained portfolio optimization problem","volume":"430","author":"Zhao","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.cie.2025.111159_b47","series-title":"2020 12th international conference on advanced computational intelligence","first-page":"30","article-title":"Solving multi-objective portfolio optimization problem based on MOEA\/D","author":"Zhao","year":"2020"},{"key":"10.1016\/j.cie.2025.111159_b48","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.119600","article-title":"Multi-source data driven cryptocurrency price movement prediction and portfolio optimization","volume":"219","author":"Zhou","year":"2023","journal-title":"Expert Systems with Applications"}],"container-title":["Computers & Industrial Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835225003055?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835225003055?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T18:42:59Z","timestamp":1747420979000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360835225003055"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":48,"alternative-id":["S0360835225003055"],"URL":"https:\/\/doi.org\/10.1016\/j.cie.2025.111159","relation":{},"ISSN":["0360-8352"],"issn-type":[{"value":"0360-8352","type":"print"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Intelligent Many-objective portfolio optimization using hybrid deep learning and evolutionary algorithm approach for advanced decision-making","name":"articletitle","label":"Article Title"},{"value":"Computers & Industrial Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cie.2025.111159","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111159"}}