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학술논문경영과학2019.12 발행

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A Scheduling Problem to Minimize Total Completion Time in a No-Wait Two-Stage Assembly-Type Flow Shop

한준희(삼성전자 DS부문 생산IT그룹); 정봉주(한남대학교); 이주용(강원대학교); 심상오(한밭대학교)

36권 4호, 1~12쪽

초록

This research investigates a no-wait two-stage assembly-type flowshop for the objective of minimizing total completion times. The first stage consists of m machines on which mtypes of components are fabricated, while the second stage has a single-machine on which thosecomponents are assembled. In the problem, the assembly operations in the second stage should be started immediately after those fabrications are completed in the first stage. This problem is modeled in a mathematical programming formulation and the optimal solutions are obtained by CPLEX. Since this problem is known to be NP-complete, heuristic algorithms are proposed to solve the large sized problem within a short computation time. Computational experiments on randomly generated problem instances are done to evaluate the performance of the algorithms and the results are reported.

Abstract

This research investigates a no-wait two-stage assembly-type flowshop for the objective of minimizing total completion times. The first stage consists of m machines on which mtypes of components are fabricated, while the second stage has a single-machine on which thosecomponents are assembled. In the problem, the assembly operations in the second stage should be started immediately after those fabrications are completed in the first stage. This problem is modeled in a mathematical programming formulation and the optimal solutions are obtained by CPLEX. Since this problem is known to be NP-complete, heuristic algorithms are proposed to solve the large sized problem within a short computation time. Computational experiments on randomly generated problem instances are done to evaluate the performance of the algorithms and the results are reported.

발행기관:
한국경영과학회
DOI:
http://dx.doi.org/10.7737/KMSR.2019.36.4.001
분류:
경영학

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대기시간을 허용하지 않는 두 단계 조립시스템에서 총 작업완료시간 최소화를 위한 일정계획 연구 | 경영과학 2019 | AskLaw | 애스크로 AI