Search Results - Dynamic constrained multi-objective optimization problems

Multi-objective optimal power flow problem using constrained dynamic multitasking multi-objective optimization algorithm by Zhu, Junhua, Yu, Xiaobing, Wang, Feng, Mao, Yaqi

“… To address constrained multi-objective optimization problems (CMOPs), a recent evolutionary multi-tasking (EMT…”
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A Coevolutionary Response Framework for Dynamic Constrained Multi-Objective Optimization Problems by Bao, Qian, Wang, Maocai, Yang, Shengxiang, Dai, Guangming, Chen, Xiaoyu

“…Dynamic constrained multi-objective optimization problems (DCMOPs) present significant challenges due to the evolving nature of both objectives and constraints…”
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Penalty and prediction methods for dynamic constrained multi-objective optimization by Wang, Fengxia, Huang, Min, Yang, Shengxiang, Wang, Xingwei

“… Dynamic constrained multi-objective optimization problems (DCMOPs) involve objective functions and constraints that vary over time, requiring optimization algorithms to track the changing Pareto optimal set (POS) quickly…”
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A novel particle swarm optimization algorithm with local search for dynamic constrained multi-objective optimization problems by Jingxuan Wei, Liping Jia

“…In the real world, many optimization problems are dynamic constrained multi-objective optimization problems…”
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Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems by Helbig, Mardé, Engelbrecht, Andries P.

“… This kind of problems is referred to as dynamic multi-objective optimisation problems (DMOOPs). Most research in multi-objective optimisation…”
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A dynamic dual-population co-evolution multi-objective evolutionary algorithm for constrained multi-objective optimization problems by Kong, Xiangsong, Yang, Yongkuan, Lv, Zhisheng, Zhao, Jing, Fu, Rong

“…Many multi-objective evolutionary algorithms are proposed to handle constrained multi-objective optimization problems…”
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A dual-population evolutionary algorithm based on dynamic constraint processing and resources allocation for constrained multi-objective optimization problems by Qiao, Kangjia, Chen, Zhaolin, Qu, Boyang, Yu, Kunjie, Yue, Caitong, Chen, Ke, Liang, Jing

“…Constrained multi-objective optimization problems (CMOPs) contain the satisfaction of various constraints and optimization of multiple objectives simultaneously, thus they are extremely challenging…”
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A dynamic tri-population multi-objective evolutionary algorithm for constrained multi-objective optimization problems by Yang, Yongkuan, Yan, Bing, Kong, Xiangsong

“…Balancing between the convergence, feasibility, and diversity of the population is the key to solving constrained multi-objective optimization problems (CMOPs…”
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Hyper rectangle search based particle swarm algorithm for dynamic constrained multi-objective optimization problems by Jingxuan Wei, Yuping Wang

“…In the real world, many optimization problems are dynamic constrained multi-objective optimization problems…”
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Feasibility-guided momentum prediction for dynamic constrained multi-objective optimization by Li, Lin, Feng, Yiqi, Guo, Yinan, Lei, Ru, Tong, Fei, Zhang, Zuowei, Cai, Linkai

“…•Extensive experiments show superior performance in convergence and adaptability. Dynamic constrained multi-objective optimization problems (DCMOPs…”
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A two-level parallel decomposition-based artificial bee colony method for dynamic multi-objective optimization problems by Bai, Yuyang, Zhang, Changsheng, Bai, Weitong

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Antenna design using dynamic multi-objective evolutionary algorithm by Jiao, Ruwang, Sun, Yongzhi, Sun, Jianqing, Jiang, Yuhong, Zeng, Sanyou

“…). Then a framework is introduced for solving the COP. The framework converts a COP into an equivalent dynamic constrained multi-objective optimisation problem (DCMOP…”
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A dynamic constrained multi-objective evolutionary algorithm with a dual prediction mechanism by Yang, Zhe, Deng, Libao, Li, Chunlei, Qin, Yifan, Zhang, Lili

“… The design of evolutionary algorithms for dynamic constrained multi-objective optimization problems is a significant research area, driven by the need for real-time adaptive solutions in complex real-world systems…”
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An Effective Dynamic Constrained Two-Archive Evolutionary Algorithm for Cooperative Search-Track Mission Planning by UAV Swarms in Air Intelligent Transportation by Zhang, Xiaojie, Zheng, Jibin, Su, Tao, Ding, Minghui, Liu, Hongwei

“… In response to tackle the problem, we model the mission planning problem in the uncertain dynamic environment as a dynamic multi-constraint and multi-objective optimization problems (DMCMOP…”
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Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging by Ma, Haiping, Yang, Zhile, You, Pengcheng, Fei, Minrui

“…), namely MO-DEELDP problem. First, a real-world economic emission load dispatch considering PEVs charging is first formulated as a constrained dynamic multi-objective optimization problem…”
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Dynamic constrained multi-objective model for solving constrained optimization problem by Sanyou Zeng, Shizhong Chen, Jiang Zhao, Aimin Zhou, Zhengjun Li, Hongyong Jing

“…Constrained optimization problem (COP) is skillfully converted into dynamic constrained multi-objective optimization problem (DCMOP) in this paper…”
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Constrained dynamic multi-objective evolutionary optimization for operational indices of beneficiation process by Yang, Cuie, Ding, Jinliang

“… Focusing on the operational indices optimization under uncertain environments in production process, this paper first formulates a constrained dynamic multi-objective optimization problem based…”
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Dynamic multi-objective differential evolution for solving constrained optimization problem by Lina Jia, Sanyou Zeng, Dong Zhou, Aimin Zhou, Zhengjun Li, Hongyong Jing

“…Dynamic constrained multi-objective differential evolution (DCMODE) is designed for solving constrained optimization problem (COP…”
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A Dynamic Penalty Function within MOEA/D for Constrained Multi-objective Optimization Problems by Maldonado, Hugo Monzon, Zapotecas-Martinez, Saul

“… (Constrained Multi-objective Optimization Problems). In this paper, we adhere to the MOEA/D framework, a simple penalty function to deal with CMOPs…”
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A survey of artificial immune algorithms for multi-objective optimization by Li, Lingjie, Lin, Qiuzhen, Ming, Zhong

“…, they are mostly designed to solve multi-objective optimization problems (MOPs), dynamic MOPs, and constrained MOPs…”
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