(A) genetic algorithm with a mendel operator for multimodal function optimization = 멀티모달 함수의 최적화를 위한 멘델연산 유전자 알고리듬

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In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional gentic algorithm(GA)s. This algorithm finds one of local optimizers first and another optimizer at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimizer again, we devise a new genetic operator, called a Mendel operator which simulates the Mendel``s genetic law. The new algorithm using the Mendel operator remembers the optimizers obtained so far, compels individuals to move away from them, and finds a new optimizer.
Advisors
Tahk, Min-Jearesearcher탁민제researcher
Description
한국과학기술원 : 항공우주공학전공,
Publisher
한국과학기술원
Issue Date
2000
Identifier
158169/325007 / 000983290
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 항공우주공학전공, 2000.2, [ [v], 34 p. ]

Keywords

Multimodal optimization; Genetic algorithm; Mendel operator; 멘델연산; 멀티모달 함수 최적화; 유전자 알고리듬

URI
http://hdl.handle.net/10203/26857
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=158169&flag=dissertation
Appears in Collection
AE-Theses_Master(석사논문)
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