两种新的选择方法及其对遗传算法求解供应链和旅行商问题性能的影响

IF 1.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Bio-Inspired Computation Pub Date : 2023-01-01 DOI:10.1504/ijbic.2023.10054864
M. Rafsanjani, S. Eskandari
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Two new selection methods and their effects on the performance of genetic algorithm in solving supply chain and traveling salesman problems
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来源期刊
International Journal of Bio-Inspired Computation
International Journal of Bio-Inspired Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.10
自引率
5.70%
发文量
37
审稿时长
>12 weeks
期刊介绍: IJBIC discusses the new bio-inspired computation methodologies derived from the animal and plant world, such as new algorithms mimicking the wolf schooling, the plant survival process, etc. Topics covered include: -New bio-inspired methodologies coming from creatures living in nature artificial society- physical/chemical phenomena- New bio-inspired methodology analysis tools, e.g. rough sets, stochastic processes- Brain-inspired methods: models and algorithms- Bio-inspired computation with big data: algorithms and structures- Applications associated with bio-inspired methodologies, e.g. bioinformatics.
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