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A study on production and distribution planning problems using hybrid genetic algorithm

  • 정성원 (서울대학교 공과대학 산업공학과/서울대학교 자동화시스템 공동연구소) ;
  • 장양자 (서울대학교 공과대학 산업공학과/서울대학교 자동화시스템 공동연구소) ;
  • 박진우 (서울대학교 공과대학 산업공학과/서울대학교 자동화시스템 공동연구소)
  • 발행 : 2001.12.01

초록

Rapid development in computer and network technology these days has created in environment in which decisions for manufacturing companies can be made in a much broader perspective. Especially, better decisions on production and distribution planning(PDP) problems can be made laking advantage of real time information from all the parties concerned. However, since the PDP problem-a core part of the supply chain management- is known to be the so-called NP-hard problem, so heuristic methods are dominantly used to find out solutions in a reasonable time. As one of those heuristic techniques, many previous studios considered genetic a1gorithms. A standard genetic a1gorithm applies rules of reproduction, gene crossover, and mutation to the pseudo-organisms so the organisms can pass along beneficial and survival-enhancing trails to a new generation. When it comes to representing a chromosome on the problem, it is hard to guarantee an evolution of solutions through classic a1gorithm operations alone, for there exists a strong epitasis among genes. To resolve this problem, we propose a hybrid genetic a1gorithm based on Silver-Meal heuristic. Using IMS-TB(Intelligent Manufacturing System Test-bed) problem sets. the good performance of the proposed a1gorithm is demonstrated.

키워드

참고문헌

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  8. 메타 휴리스틱 김여근;윤복식;이상복
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