抄録
Evolutionary Algorithms are often well-suited for optimization problems. Since the mid-1980's, interest in multiobjective problems has been expanding rapidly. Various evolutionary algorithms have been developed which are capable of searching for multiple solutions concurrently in a single run. In this paper, we proposed a genetic symbiosis algorithm (GSA) for multi-object optimization problems (MOP) based on the symbiotic concept found widely in ecosystem. In the proposed GSA for MOP, a set of symbiotic parameters are introduced to modify the fitness of individuals used for reproduction so as to obtain a variety of Pareto solutions corresponding to user's demands. The symbiotic parameters are trained by minimizing a user defined criterion function. Several numerical simulations are carried out to demonstrate the effectiveness of proposed GSA.
本文言語 | English |
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ページ | 137-142 |
ページ数 | 6 |
出版ステータス | Published - 2000 12 1 |
外部発表 | はい |
イベント | 9th IEEE International Workshop on Robot and Human Interactive Communication RO-MAN2000 - Osaka, Japan 継続期間: 2000 9 27 → 2000 9 29 |
Conference
Conference | 9th IEEE International Workshop on Robot and Human Interactive Communication RO-MAN2000 |
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Country | Japan |
City | Osaka |
Period | 00/9/27 → 00/9/29 |
ASJC Scopus subject areas
- Hardware and Architecture
- Software