Výsledky vyhľadávania - "constrained multi-objective evolutionary algorithms"

A two-phase framework of locating the reference point for decomposition-based constrained multi-objective evolutionary algorithms Autor Peng, Chaoda, Liu, Hai-Lin, Goodman, Erik D., Tan, Kay Chen

“…Reference point is a key component in decomposition-based constrained multi-objective evolutionary algorithms (CMOEAs…”
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Push and pull search for solving constrained multi-objective optimization problems Autor Fan, Zhun, Li, Wenji, Cai, Xinye, Li, Hui, Wei, Caimin, Zhang, Qingfu, Deb, Kalyanmoy, Goodman, Erik

“…This paper proposes a push and pull search (PPS) framework for solving constrained multi-objective optimization problems (CMOPs). To be more specific, the…”
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An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions Autor Fan, Zhun, Li, Wenji, Cai, Xinye, Huang, Han, Fang, Yi, You, Yugen, Mo, Jiajie, Wei, Caimin, Goodman, Erik

“…) to solve constrained multi-objective optimization problems (CMOPs). The proposed constrained multi-objective evolutionary algorithm (CMOEA…”
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MOEA/D with angle-based constrained dominance principle for constrained multi-objective optimization problems Autor Fan, Zhun, Fang, Yi, Li, Wenji, Cai, Xinye, Wei, Caimin, Goodman, Erik

“…This paper proposes a novel constraint-handling mechanism, namely the angle-based constrained dominance principle (ACDP), to solve constrained multi-objective…”
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A coevolutionary constrained multi-objective algorithm with a learning constraint boundary Autor Cao, Jie, Yan, Zesen, Chen, Zuohan, Zhang, Jianlin

“…When solving constrained multi-objective optimization problems, the balance of convergence, diversity, and feasibility plays a pivotal role. To address this…”
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Push and pull search embedded in an M2M framework for solving constrained multi-objective optimization problems Autor Fan, Zhun, Wang, Zhaojun, Li, Wenji, Yuan, Yutong, You, Yugen, Yang, Zhi, Sun, Fuzan, Ruan, Jie

“…In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the…”
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A Dual-Population Constrained Multi-Objective Evolutionary Algorithm with Success Incentive Mechanism and its application to uncertain multimodal transportation problems Autor Yang, Zhe, Deng, Libao, Di, Yuanzhu, Li, Chunlei, Qin, Yifan, Zhang, Lili

“… To solve this complex problem, this paper introduces a new algorithmic framework. The proposed algorithm, a Dual-Population Constrained Multi-Objective Evolutionary Algorithm with a Success Incentive Mechanism (DSCMOEA…”
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Competition-based two-stage evolutionary algorithm for constrained multi-objective optimization Autor Hao, Lupeng, Peng, Weihang, Liu, Junhua, Zhang, Wei, Li, Yuan, Qin, Kaixuan

“…In recent years, the emergence of constrained multi-objective evolutionary algorithms (CMOEAs…”
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A Pareto front estimation-based constrained multi-objective evolutionary algorithm Autor Cao, Jie, Yan, Zesen, Chen, Zuohan, Zhang, Jianlin

“…The balance of convergence, diversity, and feasibility plays a pivotal role in constrained multi-objective optimization problems. To address this issue, in…”
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A Review of Constrained Multi-Objective Evolutionary Algorithm-Based Unmanned Aerial Vehicle Mission Planning: Key Techniques and Challenges Autor Huang, Gang, Hu, Min, Yang, Xueying, Wang, Xun, Wang, Yijun, Huang, Feiyao

“… struggle to effectively address these difficulties. Constrained multi-objective evolutionary algorithms have been proven to be effective methods for solving complex…”
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A coevolution algorithm based on two-staged strategy for constrained multi-objective problems Autor Fan, Chaodong, Wang, Jiawei, Xiao, Leyi, Cheng, Fanyong, Ai, Zhaoyang, Zeng, Zhenhuan

“…Constrained Multiobjective Problem (CMOP) is widely used in engineering applications, but the current constrained Multiobjective Optimization algorithms…”
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A comparative study of constrained multi-objective evolutionary algorithms on constrained multi-objective optimization problems Autor Zhun Fan, Yi Fang, Wenji Li, Jiewei Lu, Xinye Cai, Caimin Wei

“… This paper first reviews a number of popular constrained multi-objective evolutionary algorithms (CMOEAs…”
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A Manipulator Design Optimization Based on Constrained Multi-objective Evolutionary Algorithms Autor Yang Xiao, Zhun Fan, Wenji Li, Shen Chen, Lei Zhao, Honghui Xie

“… Finally, constrained multi-objective evolutionary algorithms (CMOEAs) are employed to solve the formulated problem. Several reasonable optimal combinations of geometrical parameters and type selection of motor and gearbox are provided. And compare them with the original structure of UR5…”
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A double auxiliary optimization constrained multi-objective evolutionary algorithm Autor Yang, Yongkuan, Yan, Bing, Kong, Xiangsong, Zhao, Jing

“… Motivated by this inspiration, we propose a double auxiliary optimization constrained multi-objective evolutionary algorithm, namely DAO…”
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A constrained multi-objective evolutionary algorithm based on decomposition and dynamic constraint-handling mechanism Autor Yang, Yongkuan, Liu, Jianchang, Tan, Shubin

“… Some constrained multi-objective evolutionary algorithms (CMOEAs) have been developed for CMOPs, but they still suffer from the problems of easily getting trapped into local optimal solutions and low convergence…”
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A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm Autor Qiao, Kangjia, Liang, Jing, Yu, Kunjie, Wang, Minghui, Qu, Boyang, Yue, Caitong, Guo, Yinan

“… Most constrained multi-objective evolutionary algorithms (CMOEAs) are prone to fall into the local optima due to the imbalance between objectives and constraints as well as the poor search ability of the population…”
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A constrained multi-objective evolutionary algorithm with Pareto estimation via neural network Autor Liu, Zongli, Zhao, Peng, Cao, Jie, Zhang, Jianlin, Chen, Zuohan

“…) lies in achieving a balance among convergence, diversity, and feasibility. To address this issue, this paper proposes a constrained multi-objective evolutionary algorithm with Pareto estimation via neural network named CMOEA-PeNN…”
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A dual dynamic constraint boundary based constrained multi-objective evolutionary algorithm for small feasible regions Autor Zhu, Cong, Yang, Yongkuan, Kong, Xiangsong, Yang, Yanxiang

“… struggle to balance feasibility, diversity, and convergence within the population. To overcome this challenge, we propose a dual dynamic constraint boundary-based constrained multi-objective evolutionary algorithm, referred to as TPDCB…”
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A constrained multi-objective evolutionary algorithm based on fitness landscape indicator Autor Fang, Jingjing, Liu, Hai-Lin, Gu, Fangqing

“… Considering the different requirements of different problems on resource allocation of exploration and exploitation, this paper proposes a new constrained multi-objective evolutionary algorithm based…”
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A flexible two-stage constrained multi-objective evolutionary algorithm based on automatic regulation Autor Zou, Juan, Luo, Jian, Liu, Yuan, Yang, Shengxiang, Zheng, Jinhua

“…The core element in solving constrained multi-objective problems (CMOPs) with evolutionary algorithms is simultaneously balancing objective optimization and…”
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