• 산업경영시스템학회지
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• 제27권4호
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• pp.141-146
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• 2004

This research considers the problem of scheduling jobs on unrelated parallel machines with a common due date. The objective is to minimize the total absolute deviation of job completion times about the common due date. This problem is motivated by the fact that a certain phase of printed circuit board manufacturing and other production systems is bottleneck and the processing speeds of parallel machines in this phase are different for each job. A zero-one integer programming formulation is presented and two dominance properties are proved. By these dominance properties, it is shown that the problem is reduced to asymmetric assignment problem and is solvable in polynomial time.

• 산업경영시스템학회지
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• 제38권2호
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• pp.47-55
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• 2015

This paper deals with rescheduling on unrelated parallel-machines with compressible processing times, assuming that the arrival of a set of new jobs triggers rescheduling. It formulates this rescheduling problem as an assignment problem with a side constraint and proposes a heuristic to solve it. Computational tests evaluate the efficacy of the heuristic.

• 산업공학
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• 제25권3호
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• pp.357-364
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• 2012

This paper considers a unrelated parallel machine scheduling problem with ready times, due times and sequence and machine-dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of machines to minimize the total tardy time. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, a genetic algorithm using an effective dispatching method is proposed. The performance of the proposed genetic algorithm is evaluated using several randomly generated examples.

• 대한안전경영과학회지
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• 제25권2호
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• pp.1-8
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• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• 대한산업공학회지
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• 제19권4호
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• pp.125-135
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• 1993

An Unrelated Parallel Processing with Weighted jobs and Setup times scheduling prolem is studied. We consider a parallel processing in which a group of processors(machines) perform a single operation on jobs of a number of different job types. The processing time of each job depends on both the job and the machine, and each job has a weight. In addition each machine requires significant setup time between processing jobs of different job types. The performance measure is to minimize total weighted flow time in order to meet the job importance and to minimize in-process inventory. We present a 0-1 Mixed Integer Programming model as an optimizing algorithm. We also present a simple heuristic algorithm. Computational results for the optimal and the heuristic algorithm are reported and the results show that the simple heuristic is quite effective and efficient.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.311-313
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• 2023

병렬 기계 작업장에서 자원을 효율적으로 활용하기 위해서는 처리할 작업을 적절한 기계에 할당해야 한다. 특정 작업을 처리할 기계를 선택할 때 휴리스틱을 사용할 수도 있으나, 특정 작업장에 맞춤화된 휴리스틱을 개발하는 것은 쉽지 않다. 반면, 본 논문에서는 이종 병렬 기계 작업장을 위한 작업 할당 모형을 개발하는데 강화학습을 응용하고자 한다. 작업 할당 모형을 학습하는데 필요한 에피소드들은 상용 시뮬레이션 소프트웨어인 FlexSim을 이용하여 생성하였다. 아울러, stable-baseline3 라이브러리를 이용하여 강화학습 알고리즘을 생성된 에피소드들에 적용하였다. 실험 결과를 통해 시뮬레이션과 강화학습이 작업장 운영관리에 유용함을 알 수 있었다.