Evolutionary dynamic multi-objective optimisation: A survey
Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly
growing area of investigation. EDMO employs evolutionary approaches to handle multi …
growing area of investigation. EDMO employs evolutionary approaches to handle multi …
[PDF][PDF] 多目标进化算法性能评价指标研究综述
王丽萍， 任宇， 邱启仓， 邱飞岳 - 计算机学报, 2021 - cjc.ict.ac.cn
多目标进化算法性能评价指标研究综述 Page 1 第??卷第?期 计算机学报 Vol. ?? No. ? 20??年
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?月 CHINESE JOURNAL OF COMPUTERS ???. 20?? 收稿日期:年-月-日;最终修改稿收到日期 …
Multi-objective robust optimisation model for MDVRPLS in refined oil distribution
At depots with refined oil shortage, arranging a reasonable distribution scheme with limited
supply affects operation costs, demand satisfaction rate of gasoline stations …
supply affects operation costs, demand satisfaction rate of gasoline stations …
[HTML][HTML] Gene selection for microarray data classification via multi-objective graph theoretic-based method
M Rostami, S Forouzandeh, K Berahmand… - Artificial Intelligence in …, 2022 - Elsevier
In recent decades, the improvement of computer technology has increased the growth of
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …
A multipopulation multiobjective ant colony system considering travel and prevention costs for vehicle routing in COVID-19-like epidemics
As transportation system plays a vastly important role in combatting newly-emerging and
severe epidemics like the coronavirus disease 2019 (COVID-19), the vehicle routing …
severe epidemics like the coronavirus disease 2019 (COVID-19), the vehicle routing …
Interval multiobjective optimization with memetic algorithms
J Sun, Z Miao, D Gong, XJ Zeng, J Li… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
One of the most important and widely faced optimization problems in real applications is the
interval multiobjective optimization problems (IMOPs). The state-of-the-art evolutionary …
interval multiobjective optimization problems (IMOPs). The state-of-the-art evolutionary …
Dynamic multi-objective evolutionary algorithm based on knowledge transfer
L Wu, D Wu, T Zhao, X Cai, L Xie - Information Sciences, 2023 - Elsevier
Dynamic multi-objective optimization problems (DMOPs) are mainly reflected in objective
changes with changes in the environment. To solve DMOPs, a transfer learning (TL) …
changes with changes in the environment. To solve DMOPs, a transfer learning (TL) …
A multimodel prediction method for dynamic multiobjective evolutionary optimization
M Rong, D Gong, W Pedrycz… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
A large number of prediction strategies are specific to a dynamic multiobjective optimization
problem (DMOP) with only one type of the Pareto set (PS) change. However, a continuous …
problem (DMOP) with only one type of the Pareto set (PS) change. However, a continuous …
Ensemble prediction-based dynamic robust multi-objective optimization methods
Y Guo, H Yang, M Chen, J Cheng, D Gong - Swarm and evolutionary …, 2019 - Elsevier
Many real-world multi-objective optimization problems are subject to environmental changes
over time, resulting in changing Pareto-optima. Wide studies on solving dynamic multi …
over time, resulting in changing Pareto-optima. Wide studies on solving dynamic multi …
A hybrid teaching and learning-based optimization algorithm for distributed sand casting job-shop scheduling problem
H Tang, B Fang, R Liu, Y Li, S Guo - Applied Soft Computing, 2022 - Elsevier
Because of global manufacturing, the foundry production workshop has shifted from single-
factory production to multi-factory production. The distributed flexible job-shop scheduling …
factory production to multi-factory production. The distributed flexible job-shop scheduling …