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摘要:
This work investigates one immune optimization approach for dynamic constrained multi-objective multimodal optimization in terms of biological immune inspirations and the concept of constraint dominance. Such approach includes mainly three functional modules, environmental detection, population initialization and immune evolution. The first, inspired by the function of immune surveillance, is designed to detect the change of such kind of problem and to decide the type of a new environment;the second generates an initial population for the current environment, relying upon the result of detection;the last evolves two sub-populations along multiple directions and searches those excellent and diverse candidates. Experimental results show that the proposed approach can adaptively track the environmental change and effectively find the global Pareto-optimal front in each environment.
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篇名 Immune Optimization Approach for Dynamic Constrained Multi-Objective Multimodal Optimization Problems
来源期刊 美国运筹学期刊(英文) 学科 医学
关键词 DYNAMIC CONSTRAINED MULTI-OBJECTIVE OPTIMIZATION MULTIMODALITY Artificial IMMUNE Systems IMMUNE OPTIMIZATION Environmental Detection
年,卷(期) 2012,(2) 所属期刊栏目
研究方向 页码范围 193-202
页数 10页 分类号 R73
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DYNAMIC
CONSTRAINED
MULTI-OBJECTIVE
OPTIMIZATION
MULTIMODALITY
Artificial
IMMUNE
Systems
IMMUNE
OPTIMIZATION
Environmental
Detection
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期刊影响力
美国运筹学期刊(英文)
半月刊
2160-8830
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
329
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0
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0
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