Výsledky vyhľadávania - many-objective evolutionary optimization algorithm

A Cα-dominance-based solution estimation evolutionary algorithm for many-objective optimization Autor Liu, Junhua, Wang, Yuping, Cheung, Yiu-ming

“…Balancing convergence and diversity is a key issue for many-objective optimization problems (MaOPs…”
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Effect of Objective Normalization and Penalty Parameter on Penalty Boundary Intersection Decomposition-Based Evolutionary Many-Objective Optimization Algorithms Autor Chen, Lei, Deb, Kalyanmoy, Liu, Hai-Lin, Zhang, Qingfu

“…An objective normalization strategy is essential in any evolutionary multiobjective or many-objective optimization (EMO or EMaO…”
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A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization Autor Pan, Linqiang, He, Cheng, Tian, Ye, Wang, Handing, Zhang, Xingyi, Jin, Yaochu

“… This paper proposes a surrogate-assisted many-objective evolutionary algorithm that uses an artificial neural network to predict the dominance relationship between candidate solutions and reference…”
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A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization Autor Shang, Ke, Ishibuchi, Hisao

“…In this article, a new hypervolume-based evolutionary multiobjective optimization algorithm (EMOA…”
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Two reference vector sets based evolutionary algorithm for many‐objective optimization Autor Qin, Cifeng, Ming, Fei, Gong, Wenyin

“…Solving many‐objective optimization problems (MaOPs) by means of evolutionary algorithms obtains considerable attention in the community of evolutionary computation…”
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IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems Autor Sun, Yanan, Yen, Gary G., Yi, Zhang

“… In this paper, an IGD indicator-based evolutionary algorithm for solving many-objective optimization problems (MaOPs) has been proposed…”
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An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition Autor Ke Li, Deb, Kalyanmoy, Qingfu Zhang, Sam Kwong

“… Most existing methodologies, which have demonstrated their niche on various practical problems involving two and three objectives, face significant challenges in many-objective optimization…”
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A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization Autor Ran Cheng, Yaochu Jin, Olhofer, Markus, Sendhoff, Bernhard

“…In evolutionary multiobjective optimization, maintaining a good balance between convergence and diversity is particularly crucial to the performance of the evolutionary algorithms (EAs…”
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A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization Autor Zhang, Xingyi, Tian, Ye, Jin, Yaochu

“…Evolutionary algorithms (EAs) have shown to be promising in solving many-objective optimization problems (MaOPs…”
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A Grid-Based Evolutionary Algorithm for Many-Objective Optimization Autor Yang, Shengxiang, Li, Miqing, Liu, Xiaohui, Zheng, Jinhua

“… This paper proposes a grid-based evolutionary algorithm (GrEA) to solve many-objective optimization problems…”
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DCDG-EA: Dynamic convergence–diversity guided evolutionary algorithm for many-objective optimization Autor Li, Zhiyong, Lin, Ke, Nouioua, Mourad, Jiang, Shilong, Gu, Yu

“… significant challenges in case of problems with more than three objectives, namely many-objective optimization problems (MaOPs…”
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A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization Autor Yuan, Yuan, Xu, Hua, Wang, Bo, Yao, Xin

“…Many-objective optimization has posed a great challenge to the classical Pareto dominance-based multiobjective evolutionary algorithms (MOEAs…”
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A New Two-Stage Evolutionary Algorithm for Many-Objective Optimization Autor Sun, Yanan, Xue, Bing, Zhang, Mengjie, Yen, Gary G.

“…Convergence and diversity are interdependently handled during the evolutionary process by most existing many-objective evolutionary algorithms (MaOEAs…”
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A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization Autor Asafuddoula, M., Ray, Tapabrata, Sarker, Ruhul

“…Decomposition-based evolutionary algorithms have been quite successful in solving optimization problems involving two and three objectives…”
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A many-objective evolutionary algorithm based on three states for solving many-objective optimization problem Autor Zhao, Jiale, Zhang, Huijie, Yu, Huanhuan, Fei, Hansheng, Huang, Xiangdang, Yang, Qiuling

“…In recent years, researchers have taken the many-objective optimization algorithm, which can optimize 5, 8, 10, 15, 20 objective functions simultaneously, as a new research topic…”
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ESOEA: Ensemble of single objective evolutionary algorithms for many-objective optimization Autor Pal, Monalisa, Bandyopadhyay, Sanghamitra

“…Inspired by the success of decomposition based evolutionary algorithms and the necessary search for a versatile many-objective optimization algorithm which is adaptive to several kinds…”
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An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints Autor Deb, Kalyanmoy, Jain, Himanshu

“…, there is now a growing need for developing evolutionary multiobjective optimization (EMO) algorithms for handling many-objective…”
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A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization Autor Song, Zhenshou, Wang, Handing, He, Cheng, Jin, Yaochu

“…) where the function evaluations are economically/computationally expensive. Such problems pose great challenges to most existing multiobjective evolutionary algorithms (EAs…”
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Neighborhood samples and surrogate assisted multi-objective evolutionary algorithm for expensive many-objective optimization problems Autor Zhao, Yi, Zeng, Jianchao, Tan, Ying

“…Many surrogate-assisted meta-heuristic algorithms have been proposed for single-objective expensive optimization problems, however, not so much attention has been paid to multi-objective expensive…”
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Objective Space-Based Population Generation to Accelerate Evolutionary Algorithms for Large-Scale Many-Objective Optimization Autor Deng, Qi, Kang, Qi, Zhang, Liang, Zhou, MengChu, An, Jing

“…The generation and updating of solutions, e.g., crossover and mutation, of many existing evolutionary algorithms directly operate on decision variables…”
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