• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.84-92
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• 2008

Scheduling is one of the most important issues in the planning and operation of production systems. This paper investigates a general job shop scheduling problem with reentrant work flows and sequence dependent setup times. The disjunctive graph representation is used to capture the interactions between machines in job shop. Based on this representation, four two-phase heuristic procedures are proposed to obtain near optimal solutions for this problem. The obtained solutions in the first phase are substantially improved by reversing the direction of some critical disjunctive arcs of the graph in the second phase. A comparative study is conducted to examine the performance of these proposed algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.10a
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• pp.72-72
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• 1999

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.75-85
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• 1985

The application of GT results in the mass production effect to multi-product, small lot-sized production. Group scheduling, which is operations scheduling based on the GT concept, is analyzed in a multistage manufacturing system. But the research has been limited in independent setup time models. A heuristic algorithm has been developed to minimize the mean flow time when setup times are dependent to sequence of group in multistage. For evaluation of the heuristic algorithm, the solution of heuristic algorithm is compared with that of random scheduling. The result of comparison indicates that the proposed heuristic algorithm provides good solutions with relatively fewer computational effort.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.431-446
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• 1998

In this paper, we consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, we first propose a dynamic programming(DP) algorithm for sequencing jobs processed on a single machine. The algorithm is then extended to handle jobs on parallel-identical machines. Finally, we developed an improved version of the algorithm which generates optimal solutions using much smaller amount of memory space and computing time. Computational results are provided to illustrate the performance of the DP algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.13-13
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• 1988

This paper considers the sequencing problem in mixed model assembly lines with hybrid workstation types and sequence-dependent setup times. Computation time is often a critical factor in choosing a method of determining the sequence. We develop a mathematical formulation of the problem to minimize the overall length of a line, and present a tabu search technique which can provide a near optimal solution in real time. The proposed technique is compared with a genetic algorithm and a branch-and-bound method. Experimental results are reported to demonstrate the efficiency of the technique.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.327-329
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• 2023

순서 의존적 준비시간을 갖는 단일기계 생산라인에서 주어진 작업들을 효율적으로 수행하기 위해서는 최대한 동일하거나 유사한 유형의 작업물들을 연속적으로 처리하여 다음 번 작업물의 처리를 시작하기 전에 발생하는 준비시간을 최소화하여야 한다. 따라서, 대기 중인 것들 중 기계에 투입할 작업물을 적절히 선택하는 것이 중요하며, 이를 위해 작업 배정 규칙과 같은 휴리스틱을 사용할 수도 있지만, 이러한 해법들은 일반적으로 다양한 상황을 동적으로 고려하지 못하는 한계점을 갖는다. 따라서, 본 논문에서는 상용 3D 시뮬레이션 소프트웨어인 FlexSim을 사용하여 모형을 구성한 다음, 강화학습을 적용하여 대기 중인 작업물 중 최적의 후보를 선택하기 위한 작업 배정 모형을 개발하고자 한다. 세부적으로는 강화학습의 상태 및 보상을 달리 설정하면서 학습된 모형의 성능을 비교하고자 한다. 실험 결과를 통해 적절한 시뮬레이션 모형 구성과 강화학습의 파라미터 변수들을 적절히 조합하여 적절한 작업 배정 모형의 개발이 가능하다는 점을 알 수 있었다.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.121-141
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• 1989

This paper is concerned with a development and evaluation of heuristics for the multi-stage sequence dependent flowshop sequencing. Eighteen heuristics, CAM1, CAM2, and etc., are proposed. The performance measure is a makespan which is to be minimized. The experiment for each algorithm is designed for a 4*3*3 factorial design with 360 observations. The experimental factors are PS(ratio of processing times to setup times), M(number of machines), N(number of jobs). The makespan of the proposed heuristics is compared with the optimal makespan obtained by the complete enumeration of schedules. This yardstick of comparison is called a relative error. The mean relative errors of the eighteen heuristics are from 2.048% to 8.717%. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically significant at 5% level. The simulation for the large size problems is conducted to show having the similar computational results like the small size problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.79-86
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• 2012

This study focuses on the problem of scheduling wafer lots of several recipe(operation condition) types in the photolithography workstation in a semiconductor wafer fabrication facility, and sequence-dependent recipe set up times may be required at the photolithography machines. In addition, a lot is able to be operated at a machine when the reticle(mask) corresponding to the recipe type is set up in the photolithography machine. We suggest various heuristic algorithms, in which developed recipe selection rules and lot selection rules are used to generate reasonable schedules to minimizing the total weighted flowtime. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the total weighted flowtime of the wafer lots with ready times.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.107-119
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• 2004

A study on the following parallel machine problem is addressed in this research. An order is completed only when a given number of processes (cycle) are repeated. Anew cycle is possible only upon the completion of the previous cycle. Orders are classified into job group according to product feature. For a machine to switch to a different job group from the currently processing one a major setup is required while a minor setup time is inserted in between two jobs of the same job group. The objective of the study is to find a schedule that minimizes total weighted tardiness. An initial solution is obtained by the RATCS(Restricted Apparent Tardiness Cost with Setup) rule, and a Tabu search is applied to improve the solution. Numerical examples are also presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.157-160
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• 2000

This study is concerned with how to optimize the Input sequence of product models with sequence -dependent setup time in Mixed-Model Assembly Line (MMAL) using conveyor system. Usually MMAL consists of a number of stations linked by conveyor belt and each station has a work zone limited by upstream and downstream boundaries. To avoid improper interference between operators in the adjacent stations and excess of machine moving range, operators are forced to complete their operations within their predetermined work zone. In this study, our goal is to determine sequence of models for minimizing the total work unfinished within their work zone. A generalized formulation of the product sequencing problem in MMAL is presented and we developed an optimal procedure using Branch & Bound. Also we developed a heuristic procedure using local search.