Abstract
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.
| Original language | English |
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| Title of host publication | Robot and Human Communication - Proceedings of the IEEE International Workshop |
| Pages | 137-142 |
| Number of pages | 6 |
| Publication status | Published - 2000 |
| Event | 9th IEEE International Workshop on Robot and Human Interactive Communication RO-MAN2000 - Osaka, Japan Duration: Sept 27 2000 → Sept 29 2000 |
Other
| Other | 9th IEEE International Workshop on Robot and Human Interactive Communication RO-MAN2000 |
|---|---|
| Country/Territory | Japan |
| City | Osaka |
| Period | 9/27/00 → 9/29/00 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Software