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Efficient Algorithms for Solving Facility Layout Problem Using a New Neighborhood Generation Method Focusing on Adjacent Preference
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  • Efficient Algorithms for Solving Facility Layout Problem Using a New Neighborhood Generation Method Focusing on Adjacent Preference
  • Efficient Algorithms for Solving Facility Layout Problem Using a New Neighborhood Generation Method Focusing on Adjacent Preference
저자명
Fukushi. Tatsuya,Yamamoto. Hisashi,Suzuki. Atsushi,Tsujimura. Yasuhiro
간행물명
Industrial engineering & management systems : an international journal
권/호정보
2009년|8권 1호|pp.22-28 (7 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

We consider facility layout problems, where mn facility units are assigned into mn cells. These cells are arranged into a rectangular pattern with m rows and n columns. In order to solve this cell type facility layout problem, many approximation algorithms with improved local search methods were studied because it was quite difficult to find exact optimum of such problem in case of large size problem. In this paper, new algorithms based on Simulated Annealing (SA) method with two neighborhood generation methods are proposed. The new neighborhood generation method adopts the exchanging operation of facility units in accordance with adjacent preference. For evaluating the performance of the neighborhood generation method, three algorithms, previous SA algorithm with random 2-opt neighborhood generation method, the SA-based algorithm with the new neighborhood generation method (SA1) and the SA-based algorithm with probabilistic selection of random 2-opt and the new neighborhood generation method (SA2), are developed and compared by experiment of solving same example problem. In case of numeric examples with problem type 1 (the optimum layout is given), SA1 algorithm could find excellent layout than other algorithms. However, in case of problem type 2 (random-prepared and optimum-unknown problem), SA2 was excellent more than other algorithms.