An adaptive multiobjective evolutionary algorithm for dynamic multiobjective flexible scheduling problem
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23090
Abstract: There are various uncertain disturbances in the actual manufacturing environment, which makes dynamic multiobjective flexible scheduling problem of flexible job shop (MDFJSP) become the research focus in the field of optimal scheduling. In this paper,… read more here.
Keywords: dynamic multiobjective; scheduling; multiobjective flexible; scheduling problem ... See more keywords
A prediction method based on fractional order displacement for dynamic multiobjective optimization.
Sign Up to like & getrecommendations! Published in 2022 at "ISA transactions"
DOI: 10.1016/j.isatra.2022.03.015
Abstract: Prediction-based methods have become more popular for solving dynamic multiobjective optimization problems. However, most of these proposed methods only use the optimal solutions in the previous two or three environments to predict the new optimal… read more here.
Keywords: multiobjective optimization; prediction method; method; optimal solutions ... See more keywords
A Novel Dynamic Multiobjective Optimization Algorithm With Hierarchical Response System
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Computational Social Systems"
DOI: 10.1109/tcss.2023.3293331
Abstract: In this article, a novel dynamic multiobjective optimization algorithm (DMOA) is proposed based on a designed hierarchical response system (HRS). Named HRS-DMOA, the proposed algorithm mainly aims at integrating merits from the mainstream ideas of… read more here.
Keywords: novel dynamic; response; hierarchical response; dynamic multiobjective ... See more keywords
A Fast Dynamic Evolutionary Multiobjective Algorithm via Manifold Transfer Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2020.2989465
Abstract: Many real-world optimization problems involve multiple objectives, constraints, and parameters that may change over time. These problems are often called dynamic multiobjective optimization problems (DMOPs). The difficulty in solving DMOPs is the need to track… read more here.
Keywords: fast dynamic; optimization; transfer learning; dynamic multiobjective ... See more keywords
Inverse Gaussian Process Modeling for Evolutionary Dynamic Multiobjective Optimization.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3070434
Abstract: For dynamic multiobjective optimization problems (DMOPs), it is challenging to track the varying Pareto-optimal front. Most traditional approaches estimate the Pareto-optimal sets in the decision space. However, the obtained solutions do not necessarily satisfy the… read more here.
Keywords: optimization; inverse; dynamic multiobjective; decision ... See more keywords