• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.1-22
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• 2005

This paper presents new scheduling heuristics, namely Mean Progressive Weighted Tardiness Estimator (MPWT) Heuristic Method and modified priority rules with sequence-dependent setup times consideration. These are designed to solve job shop scheduling problems with new performance measures - progressive weighted tardiness penalties. More realistic constraints, which are inter-machine overlapping sequence-dependent setup times, are considered. In real production environments, inter-machine overlapping sequence-dependent setups are significant. Therefore, modified scheduling generation algorithms of active and nondelay schedules for job shop problems with inter-machine overlapping sequence-dependent setup times are proposed in this paper. In addition, new customer-based measures of performance, which are total earliness and progressive weighted tardiness, and total progressive weighted tardiness, are proposed. The objective of the first experiment is to compare the proposed priority rules with the consideration of sequence-dependent setup times and the standard priority rules without setup times consideration. The results indicate that the proposed priority rules with setup times consideration are superior to the standard priority rules without the consideration of setup times. From the second experiment and the third experiment to compare the proposed MPWT heuristic approach with the efficient priority rules with setup times consideration, the MPWT heuristic method is significantly superior to the Batched Apparent Tardiness Cost with Sequence-dependent Setups (BATCS) rule, and other priority rules based on total earliness and progressive weighted tardiness, and total earliness and tardiness.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.98-103
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• 2006

In this research, the single machine capacitated lot-sizing and scheduling problem with sequence- dependent setup costs and setup times (CLSPSD) is considered. This problem is the extension of capacitated lot-sizing and scheduling problem (CLSP) with an additional assumption on sequence-dependent setup costs and setup times. The objective of the problem is minimizing the sum of production costs, inventory holding costs and setup costs satisfying customers' demands. It is known that the CLSPSD is NP-hard. In this paper, the MIP formulation is presented. To handle the problem more efficiently, a conceptual model is suggested, and one of the well-known meta-heuristics, the simulated annealing approach is applied. To illustrate the performance of this approach, various instances are tested and the results of this algorithm are compared with those of the CLPEX. Computational results show that this approach generates optimal or nearly optimal solutions.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.87-96
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• 2001

This paper considers the transfer batch scheduling problem for a two-machine flow shop with setup times consisting of attached setup time and separate setup time. The attached setup is attached to the processing and can be scheduled in anticipation of arriving work. Two cases of the separate setup are addressed. One is the case that the separate setup can be done only when a machine is idle. The other is the case that the separate setup can be done even though the machine is idle. the other is the case that the separate setup can be done even though the machine is operating. A scheduling rule similar to Johnson\`s rule is suggested to minimize makespan. the scheduling rule developed can be applied to most of the two-machine flow shop scheduling problems if some parameters are adjusted. A numerical example is presented to illustrate the scheduling rule.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.83-91
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• 2014

We consider the problem of scheduling identical jobs with sequence-independent setup times on parallel machines. The objective is to minimize total completion times. We present the pseudopolynomial-time algorithm for the case with a fixed number of machines and an efficient approximation algorithm for our problem with identical setup times, which is known to be NP-hard even for the two-machine case.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.29-36
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• 2013

This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.91-100
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• 1990

This paper is concerned with the development of optimal algorithms for multi-stage flowshop scheduling problems with sequence dependent setup times. In the previous researches the setup time of a job is considered to be able to begin at the earliest opportunity given a particular sequence at the start of operations. In this paper the setup time of a job is considered to be able to begin only at the completion of that job on the previous machine to reflect the effects of the setup time to the performance measure of sequence dependent setup time flowshop scheduling. The results of the study consist of two areas; first, a general integer programming(IP) model is formulated and a nixed integer linear programming(MILP) model is also formulated by introducing a new binary variable. Second a depth-first branch and bound algorithm is developed. To reduce the computational burdens we use the best heuristic schedule developed by Choi(1989) as the first trial. The experiments for developed algorithm are designed for a 4$\times$3$\times$3 factorial design with 360 observations. The experimental factors are PS(ratio of processing time to setup time), M(number of machines), N(number of jobs).

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.35-47
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• 1989

This paper is concerned with a development and evaluation of heuristic algorithms for the n-job, M-stage flowshop with sequence dependent setup times. Three heuristic algorithms, CAIDAN, DANNEN and PETROV, are proposed. The makespan is taken as a performance measure for the algorithms. The experiment for each algorithm is designed for a $4{\times}3{\times}3$ factorial design with 360 observations. The experimental factors are PS (ratio of processing times to setup times), M (number of machines), and N (number of jobs). The makespan of the proposed heuristic algorithms is compared with the optimal makespan obtained by the complete enumeration method. The result of comparision of performance measure is called a relative error. The mean relative errors of CAIDAN, DANNEN and PETROV algorithms are 4.488%. 6.712% and 7.282%, respectively. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically signiticant at 5% level.

• Management Science and Financial Engineering
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• v.4 no.2
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• pp.15-42
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• 1998

A joint problem of order delivery, setup reduction, and cost-sharing in a two-echelon inventory system in which a vendor supplies multiple products to a group of buyers is studied here. The basic premise is that buyers have independently implemented setup reduction programs to acquire benefits from small order sizes. Doing so, however, causes the buyers' individually optimal order cycles to be differ from that of the vendor. In conjunction with this, two models are considered. In the first model, a multi-buyers single product situation is considered in which the vendor implements a joint supply cycle policy. However, buyers, as the dominant party, insist after implementing the individually optimal setup reduction that the vendor accept their individually optimal order schedules. In the second model. a multi-products, single buyer situation is considered in which the buyer implements a joint order policy. Here, the vendor, as the dominant party, refuses to cooperate fully with the buyer's individually reduced joint order schedule, and designs his own individually optimal setup reduction mix for each product under a given budget constraint. This led to a study of an integrated Setup Reduction/Break-even Pricing Policy for each situation to eliminate mismatches in individually optimal cycle times.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.49-64
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• 2000

A vendor supplies a product to a sole/major buyer on a lot-for-lot basis under deterministic inventory control conditions. The basic premise is that the setup cost reduction technologies are available to both the buyer and the vendor, and that the vendor's inventory and setup reduction investment costs differ from the buyer's. Therefore, an individually designed ordering and setup cost reduction policy will likely cause mismatches between the vendor's and the buyer's optimal cycle times. For this situation, we show that a joint optimal setup cost reduction and ordering policy, together with an appropriate side payment(quantity discount or premium price) schedule, can be designed in a spirit in a spirit of coordination to eliminate mismatches in individual optimal cycle times.