Search Results - "Dynamic multi-objective optimisation algorithm"

Performance measures for dynamic multi-objective optimisation algorithms by Helbig, Mardé, Engelbrecht, Andries P.

“…•We provide a comprehensive overview of MOO performance measures.•These measures are adapted and used for dynamic MOO.•We provide a comprehensive overview of…”
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Dynamic multi-objective optimization algorithm based decomposition and preference by Hu, Yaru, Zheng, Jinhua, Zou, Juan, Jiang, Shouyong, Yang, Shengxiang

“…Most of the existing dynamic multi-objective evolutionary algorithms (DMOEAs) are effective, which focuses on searching for the approximation of Pareto-optimal…”
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A dynamic multi-objective optimization algorithm based on probability-driven prediction and correlation-guided individual transfer: PDP&CGIT: A Dynamic Multi-Objective Optimization Algorithm by Ge, Fangzhen, Zhao, Xuan, Chen, Debao, Shen, Longfeng, Liu, Huaiyu

“… To this end, this study proposes a dynamic multi-objective optimization algorithm based on probability-driven prediction and correlation-guided individual transfer (PDP&CGIT…”
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Dynamic Multiobjective Optimization Algorithm Guided by Recurrent Neural Network by Hu, Yaru, Ou, Junwei, Nagaratnam Suganthan, Ponnuthurai, Pedrycz, Witold, Wang, Rui, Zheng, Jinhua, Zou, Juan, Song, Yanjie

“…In recent years, prediction-based algorithms have attracted much attention for solving dynamic multiobjective optimization (DMO) problems in the evolutionary…”
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Hybrid response dynamic multi-objective optimization algorithm based on multi-arm bandit model by Hu, Xiaolin, Wu, Lingyu, Han, Mingzhang, Zhao, Xinchao, Sang, Xinzhu

“… To address this issue, this paper proposes a hybrid response dynamic multi-objective optimization algorithm…”
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A change severity degree-based dynamic multi-objective optimization algorithm with adaptive response strategy by Kouka, Najwa, Fourati, Rahma, Fdhila, Raja, Hussain, Amir, Alimi, Adel M.

“…Many real-world optimization problems are dynamic by nature, exhibiting temporal variations in objective functions, constraints, and parameters. These problems…”
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A self-adaptive dynamic multi-objective optimization algorithm based on transfer learning and elitism-based mutation by Zhang, Xi, Jin, Yaochu, Qian, Feng

“…Dynamic multi-objective optimization problems (DMOPs) involve several conflicting objectives, and these objective functions change over time. Therefore,…”
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A dynamic multi-objective optimization algorithm with a dual mechanism based on prediction and archive by Wang, Maocai, Li, Bin, Dai, Guangming, Song, Zhiming, Chen, Xiaoyu, Bao, Qian, Peng, Lei

“…In the dynamic multi-objective optimization problems, if the environmental changes are detected, an appropriate response strategy be employed to respond…”
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Dynamic multi-objective optimization algorithm based on incremental Gaussian mixture model by Xia, Xuewen, Zeng, Yi, Xu, Xing, Zhang, Yinglong

“…In recent years, prediction-based algorithms have made significant progress in solving dynamic multi-objective optimization problems (DMOPs). However, most…”
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Dynamic multi-objective optimization algorithm via historical collaborative strategy and interval prediction strategy by Ou, Junwei, Li, Yana, Hu, Yaru, Peng, Jiankang, Zheng, Jinhua, Zou, Juan, Yang, Shengxiang

“…Dynamic multi-objective optimization problems (DMOPs) involve scenarios where objective functions, decision variables, parameters, or other elements vary over…”
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A dynamic multi-objective optimization algorithm based on probability-driven prediction and correlation-guided individual transfer by Ge, Fangzhen, Zhao, Xuan, Chen, Debao, Shen, Longfeng, Liu, Huaiyu

“… To this end, this study proposes a dynamic multi-objective optimization algorithm based on probability-driven prediction and correlation-guided individual transfer (PDP&CGIT…”
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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Li, Sanyi, Hou, Wenjie, Liu, Peng, Yue, Weichao, Wang, Qian

“…This paper introduces a special points and neural network- based dynamic multi-objective optimization algorithm (SPNN-DMOA…”
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An Adaptive Overcurrent Protection Method for Distribution Networks Based on Dynamic Multi-Objective Optimization Algorithm by Xu, Biao, Ouyang, Fan, Li, Yangyang, Yu, Kun, Ao, Fei, Li, Hui, Tan, Liming

“…With the large-scale integration of renewable energy into distribution networks, traditional fixed-setting overcurrent protection strategies struggle to adapt…”
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A Dynamic Multi-Objective Optimization Algorithm for AGV Routing in Assembly Workshops by Chen, Yong, Sun, Yuqi, Chen, Mingyu, Yi, Wenchao, Pei, Zhi, Li, Jiong

“…This study tackles the complex challenge of dynamic multi-objective vehicle routing optimization in large-scale equipment manufacturing, where routing…”
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Evolutionary dynamic multi-objective optimization algorithm based on Borda count method by Orouskhani, Maysam, Teshnehlab, Mohammad, Nekoui, Mohammad Ali

“…In this paper, a novel dynamic multi-objective optimization algorithm is introduced…”
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Analysing the performance of dynamic multi-objective optimisation algorithms by Helbig, Marde, Engelbrecht, Andries P.

“… Analysing the performance of a dynamic multi-objective optimisation algorithm (DMOA) is not a trivial task…”
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A novel cooperative coevolutionary dynamic multi-objective optimization algorithm using a new predictive model by Liu, Ruochen, Chen, Yangyang, Ma, Wenping, Mu, Caihong, Jiao, Licheng

“… In this paper, a novel cooperative coevolutionary dynamic multi-objective optimization algorithm (PNSCCDMO) is proposed…”
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An orthogonal predictive model-based dynamic multi-objective optimization algorithm by Liu, Ruochen, Niu, Xu, Fan, Jing, Mu, Caihong, Jiao, Licheng

“…In this paper, a new dynamic multi-objective optimization evolutionary algorithm is proposed for tracking the Pareto-optimal set of time-changing…”
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Dynamic multi-objective optimization algorithm based on prediction strategy by Li, Er-Chao, Ma, Xiang-Qi

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Dynamic Multi-Objective Optimization Algorithm Based on Artificial Physics Optimization by Wang, Yan, Wu, Jian, Ding, Jianguo, Wang, Haibo

“…In the context of complex optimization problems, static optimization algorithms often struggle to adapt to the rapidly evolving search space and…”
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