Results 11 to 20 of about 4,635,823 (252)
Analysing the Robustness of NSGA-II under Noise [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2023 Runtime analysis has produced many results on the efficiency of simple evolutionary algorithms like the (1+1) EA, and its analogue called GSEMO in evolutionary multiobjective optimisation (EMO).
D. Dang +3 more
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IEEE Open Journal of the Communications Society, 2022 Optimum controller placement in the presence of several conflicting objectives has received significant attention in the Software-Defined Wide Area Network (SD-WAN) deployment.
Oladipupo Adekoya, Adel Aneiba
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PLoS ONE, 2021 In order to solve the problem of unbalanced workload of employees in parallel flow shop scheduling, a method of job standard balance is proposed to describe the work balance of employees. The minimum delay time of completion and the imbalance of employee
Zhengyu Hu +3 more
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Mathematics, 2023 Recently, many-objective optimization problems (MaOPs) have become a hot issue of interest in academia and industry, and many more many-objective evolutionary algorithms (MaOEAs) have been proposed.
Yingxin Zhang, Gaige Wang, Hongmei Wang
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Journal of Marine Science and Engineering, 2022 As maritime transportation develops, the pressure of port traffic increases. To improve the management of ports and the efficiency of their operations, vessel scheduling must be optimized.
Xing Jiang +5 more
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Optimal Bespoke CDO Design via NSGA-II [PDF]
Journal of Applied Mathematics and Decision Sciences, 2009 This research work investigates the theoretical foundations and computational aspects of constructing optimal bespoke CDO structures. Due to the evolutionary nature of the CDO design process, stochastic search methods that mimic the metaphor of natural biological evolution are applied.
Jewan, Diresh +2 more
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NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems
IEEE Access, 2020 In the last two decades, the non-dominated sorting genetic algorithm II (NSGA-II) has been the most widely-used evolutionary multi-objective optimization (EMO) algorithm.
Lie Meng Pang, Hisao Ishibuchi, Ke Shang
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A First Runtime Analysis of the NSGA-II on a Multimodal Problem [PDF]
IEEE Transactions on Evolutionary Computation, 2022 Very recently, the first mathematical runtime analyses of the multiobjective evolutionary optimizer nondominated sorting genetic algorithm II (NSGA-II) have been conducted. We continue this line of research with a first runtime analysis of this algorithm
Zhongdi Qu, Benjamin Doerr
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IEEE Access, 2020 This paper develops an improved non dominated sorting genetic algorithm II (NSGA-II) based on objective importance vector γ, abbreviated as γ-NSGA-II. Different importance levels for the multiple objectives are incorporated in the objective
Lu Zhang +5 more
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Computing Offloading Strategy for Concurrent Flow Tasks Based on Two-stage Optimization [PDF]
Jisuanji gongcheng, 2022 Recently, computing offloading has attracted the attention of researchers as one of the most critical technologies in mobile edge computing. However, the existing research rarely considers the application topology, diversity of optimization objectives ...
YAO Zheng, WU Huaiyu, CHEN Yang
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