• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.419-432
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• 2005

In this paper we study the no-wait or no-idle permutation flowshop scheduling problem with an increasing and decreasing series of dominating machines. The objective is to minimize one of the five regular performance criteria, namely, total weighted completion time, maximum lateness, maximum tardiness, number of tardy jobs and makespan. We establish that these five cases are solvable by presenting a polynomial-time solution algorithm for each case.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.115-127
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• 1996

Based on a job insertion method, we developed a heuristic algorithm for the mean flowtime objective in a permutation flowshop environment. The simulation experiments are implemented to evaluate the effectiveness of the proposed algorithm against the existing heuristics. The experiments reveal the superiority of the proposed algorithm to other heuristics especially when the ratio of the number of jobs and number of machines is greater than or equal to two.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.1-17
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• 2015

In this research, we develop and suggest branch and bound algorithms for a two-machine permutation flowshop scheduling problem with the objective of minimizing makespan. In this scheduling problem, after each job is operated on the machine 1 (first machine), the job has to start its second operation on machine 2 (second machine) within its corresponding limited waiting time. In addition, each job has its corresponding ready time at the machine 1. For this scheduling problem, we develop various dominance properties and three lower bounding schemes, which are used for the suggested branch and bound algorithm. In the results of computational tests, the branch and bound algorithms with dominance properties and lower bounding schemes, which are suggested in this paper, can give optimal solution within shorter CPU times than the branch and bound algorithms without those. Therefore, we can say that the suggested dominance properties and lower bounding schemes are efficient.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.1-9
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• 2010

In this paper, we consider a two-machine re-entrant permutation flowshop scheduling problem with the objective of minimizing total flowtime, and suggest branch and bound algorithms for the scheduling problem. In this scheduling problem, each job must be processed twice on each machine, that is, each job should be processed on the two machines in the order of machine 1, machine 2 and then machine 1 and machine 2. In this research, based on the results of existing researches for re-entrant permutation flowshop scheduling problems, various dominance properties, lower bound and heuristic algorithm are suggested for the problem, and those are used to develop branch and bound algorithms. In the computational experiments for evaluation of the performance of the algorithms, the suggested branch and bound algorithms are tested on randomly generated test problems and results are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.25-32
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• 1998

A modified simulated annealing algorithm is proposed and applied to the permutation flowshop scheduling with the makespan objective. Based on the job deletion and insertion method, a newly defined Max-min perturbation scheme is proposed to obtain a better candidate solution in the simulated annealing process. The simulation experiments are conducted to evaluate the effectiveness of the proposed algorithm against the existing heuristics and results are reported.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.134-139
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• 2011

The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.33-46
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• 2000

The problem of scheduling n independent jobs on serial stages with identical parallel machines at each stage is considered. Each job lot is allocated evenly to all machines at each stage for processing and moved in transfer batches between states., This scheduling strategy is called an identical production pattern. The objective is to find a permutation schedule that minimizes makespan. A branch and bound algorithm is suggested to find an optimal permutation schedule for a transformed problem A number examples is presented to illustrate the branch and bound algorithm, Computational results for 640 problems generated randomly show that within a resonable time the suggested algorithm can be used for transfer batch scheduling in a flexible flowshop.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.115-121
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• 2007

In this paper, we study flowshop scheduling problems with availability constraints. In such problems, n jobs have to be scheduled on m machines sequentially under assumption that the machines are unavailable during some periods of planning horizon. The objective of the problem is to find a non-permutation schedule which minimizes the makespan. As a solution procedure, we propose an improved genetic algorithm which utilizes a look-ahead schedule generator to find good solutions in a reasonable time Computational experiments show that the proposed genetic algorithm outperforms the existing genetic algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.24-28
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• 2004

This paper considers a scheduling problem concerned with an assembly system where two components are first treated In their own parallel machines and then pulled to be assembled into a final product at a single assembly machine. The objective measure is the mean completion time of jobs(a finite number of products). Through characterizing solution properties, we obtain the worst case error bounds of an arbitrary permutation and a SPT based heuristic.