Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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Hybrid Approach for Solving Manufacturing Optimization Problems

제조최적화문제 해결을 위한 혼합형 접근법

  • Received : 2015.11.20
  • Accepted : 2015.12.11
  • Published : 2015.12.31
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Abstract

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

제조최적화 문제는 비선형 형태의 설계변수로 표시되며, 다양하고 복잡한 제약들을 만족하는 조건하에서 최적해를 구하는 문제이다. 이러한 제조최적화 문제 해결을 위하여 본 연구에서는 혼합형접근법을 제안한다. 제안된 혼합형접근법은 기존의 유전알고리즘(Genetic algorithm: GA)과 쿠쿠탐색(Cuckoo search: CS) 및 언덕오르기법(Hill climbing method: HCM)을 혼합한 형태로 구성된다. 제안된 혼합형접근법에서 GA는 전역적탐색(Global search)를 위해 사용되고, CS는 GA탐색과정에서 발생하는 단점을 개선하기 위해 적용되고, 마지막으로 HCM은 GA와 CS 탐색 이후의 수렴된 지역을 정밀하게 탐색하기 위한 지역적탐색(Local search)을 위해 적용된다. 실험분석에서는 다양한 형태의 제조최적화 문제가 제시되어 본 연구에서 제안된 혼합형접근법와 기존접근법들의 수행도를 각각 비교, 분석하였으며, 그 결과는 본 연구에서 제안한 혼합형접근법의 수행도가 기존접근법들의 수행도보다 더 우수한 것을 확인하였다.

Keywords

References

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