• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.67-95
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• 1998

This research addresses flow time prediction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to develop the job flow time prediction model in the dynamic unbalance djob shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc, are considered in the prediction model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness (MAL) and Mean Relative Error (MRE) are used to compare and evaluate alternative regression models devloped in this research.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.99-102
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• 2000

전통적인 job shop 일정계획문제는 NP_hard 문제로 조합최적화 문제이다 일반적인 가정은 job이 방문하는 기계들의 경로가 고정되어 있다는 것이다. 경로 유연성을 가지는 job shop 일정계획문제는 job이 방문하는 기계들의 경로가 고정되어져 있지 않다는 것이다. 이러한 경우에 전통적인 job shop 문제를 복잡하게 만든다. 경로 유연성을 가지는 job shop 문제도 NP-hard 문제이다. 그러므로 휴레스틱이나 AI 기법들을 사용하는 하는 것이 불가피하게 되었다. 유전 알고리즘은 매우 복잡한 조합 최적화문제인 job shop 일정계획문제에 적용되어지고 있다. 이 논문은 최대완료시간(makespan)으로 경로 유연성을 가지는 job shop 일정계획문제를 풀기 위한 유전 알고리즘을 제시하고자 한다. 먼저 경로 유연성을 가지는 job shop 일정계획문제에 대한 정의를 내리고 유전 알고리즘을 구축하기 위한 첫 단계로 유전적 표현 즉, 개체 표현방법에 대해 설명하고 유전 연산자의 소개 그리고 알고리즘 재생과정을 제시하고 수치실험을 통해 알고리즘이 양질의 일정계획을 찾을 수 있다는 것을 보이고자 한다.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.813-820
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• 2005

To develop a genetic algorithm about job shop scheduling with alternative routing, we are performed that genetic algorithm efficiency analysis of job shop scheduling with alternative routing, First, we proposed genetic algorithm for job shop scheduling with alternative routing. Second, we applied genetic algorithm to traditional benchmak problem appraise a compatibility of genetic algorithm. Third, we compared with dispatching rule and genetic algorithm result for problem Park[3].

• Journal of the Korean Society of Industry Convergence
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• v.4 no.3
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• pp.281-287
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• 2001

Traditional job shop scheduling is supposed that machine has a fixed processing job type. But actually the machine has a highly utilization or long processing time is occurred delay. Therefore product system is difficult to respond quickly to the change of products or loads or machine failure etc. Here we use flexible job shop which is supposed that a machine has several jobs by tool change. The heuristic for the flexible job shop scheduling has to solve two problems. One is a routing problem which is determine a machine to process job. The other is sequencing problem which is determine processing sequence. The approach to solve two problems arc a hierarchical approach which is determined routing and then schedule, and a concurrence approach which is solved concurrently two problems by considering routing when it is scheduled. In this study, we simulate for flexibility efficiency fo flexible job shop scheduling with machine failure using hierarchical approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.231-242
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• 1997

This paper describe an approximation method for solving the minimum makespan problem of job shop scheduling with fuzzy processing time. We consider the multi-part production scheduling problem in a job shop scheduling. The job shop scheduling problem is a complex system and a NP-hard problem. The problem is more complex if the processing time is imprecision. The Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Lee-Li fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study propose heuristic algorithm solving the job shop scheduling problem under fuzzy environment. In This study the proposed algorithm is designed to treat opinions of experts, also can be used to solve a job shop environment under the existence of alternate operations. On the basis of the proposed method, an example is presented.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.91-98
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• 2002

In the study, we propose, for the practical approaches of job shop scheduling, the new dispatching rules of Job shop scheduling in order to complement the practical applications in the existing researches. The performance of the new dispatching rules is compared and analyzed with the existing methods through the computer experiments in the assumed conditions. The results can be useful to improving a field application of the job shop scheduling.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.59-68
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• 2001

The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results were compared with another genetic algorithm0-based scheduling method. Compared to traditional genetic, algorithm, the proposed approach yields significant improvement at a solution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.3
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• pp.41-49
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• 2002

In the study, for the practical approaches of job shop scheduling, we propose the new dispatching rules of job shop scheduling in order to complement the practical applications in the existing researches. The assumed situation for the practical approaches considers the following; relaxation of assumption for capacity constraint by machine flexibility, the addition of the common use of jig and fixture, unbalanced machine workloads and duedate tightness, and produces fast rescheduling that reflects unexpected situations. The performance of the new dispatching rules is compared and analyzed with the existing methods through the computer experiments in the assumed conditions. The results can be useful to improving a field application of the job shop scheduling.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1095-1098
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• 1993

This paper presents linear programming neural networks for job-shop scheduling. The starting times of tasks and constraints are formulated as the linear programming problem. A modified Hopfield neural network is proposed for solving job-shop scheduling.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.49-49
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• 2004