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Two-Phase Genetic Algorithm for Solving the Paired Single Row Facility Layout Problem
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  • Two-Phase Genetic Algorithm for Solving the Paired Single Row Facility Layout Problem
  • Two-Phase Genetic Algorithm for Solving the Paired Single Row Facility Layout Problem
저자명
Parwananta. Hutama,Maghfiroh. Meilinda F.N.,Yu. Vincent F.
간행물명
Industrial engineering & management systems : an international journal
권/호정보
2013년|12권 3호|pp.181-189 (9 pages)
발행정보
대한산업공학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

This paper proposes a two-phase genetic algorithm (GA) to solve the problem of obtaining an optimum configuration of a paired single row assembly line. We pair two single-row assembly lines due to the shared usage of several workstations, thus obtaining an optimum configuration by considering the material flow of the two rows simultaneously. The problem deals with assigning workstations to a sequence and selecting the best arrangement by looking at the length and width for each workstation. This can be considered as an enhancement of the single row facility layout problem (SRFLP), or the so-called paired SRFLP (PSRFLP). The objective of this PSRFLP is to find an optimal configuration that seeks to minimize the distance traveled by the material handler and even the use of the material handler itself if this is possible. Real-world applications of such a problem can be found for apparel, shoe, and other manual assembly lines. This research produces the schematic representation solution using the heuristic approach. The crossover and mutation will be utilized using the schematic representation solution to obtain the neighborhood solutions. The first phase of the GA result is recorded to get the best pair. Based on these best matched pairs, the second-phase GA can commence.