공구유연성과 공구관련제약을 고려한 통합공정일정계획을 위한 유전알고리즘

• 영문명: An Improved Genetic Algorithm for Integrated Planning and Scheduling Algorithm Considering Tool Flexibility and Tool Constraints
• 발행기관: 한국산업경영시스템학회
• 저자명: 김영남(Young Nam Kim) 하정훈(Chung hun Ha)
• 간행물 정보: 『산업경영시스템학회지』제40권 제2호, 111~120쪽, 전체 10쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2017.06.30

영문 초록

This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.

목차

1. Introduction

2. IPPS Problem

3. Proposed Genetic Algorithm

4. Experimental Results

5. Conclusion

Acknowledgement

References

키워드

Integrated Process Planning and Scheduling Genetic Algorithm Inferior Selection