• 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 Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• 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.

• 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 Institute of Industrial Engineers
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• v.25 no.3
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• pp.360-368
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• 1999

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, a hybrid genetic algorithm is proposed. The algorithm combines a genetic algorithm for global search and a heuristic for local optimization to improve the speed of evolution convergence. The genetic operators are developed such that parallel machines can be handled in an efficient and effective way. For local optimization, the adjacent pairwise interchange method is used. The proposed hybrid genetic algorithm is compared with two heuristics, the nearest setup time method and the maximum penalty method. Computational results for a series of randomly generated problems demonstrate that the proposed algorithm outperforms the two heuristics.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.65-74
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• 1993

In this paper, a two-echelon production-inventory model is developed which integrates the production scheduling problem of the multi-products produced on a single facility and the inventory problem of the related raw materials. The setup costs of the final products are assumed to be dependent on the production sequence. The aim is to determine simultaneously the production cycle time and the production sequence of the final products, and the procurement cycle times of the raw materials. For the model developed, a solution algorithm is suggested and illustrated with a numerical example. And the result is compared with those obtained by two separate subproblems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.115-123
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• 1994

Group scheduling, which is a kind of operations scheduling based on the GT concept is analyzed in a multi-stage manufacturing system. The purpose of this research is to develop and evaluate a heuristic algorithm for determining gro up sequence and job sequence within each group to minimize a complex cost function, i.e. the sum of the total pe-nalty cost for tardiness and the total holding cost for flow time, in a multi-stage manufacturing system with group setup time dependent upon group sequence. A heuristic algorithm for group sc heduling is developed, and a numerical example is illustrated. For the evaluation of the pro-posed heuristic algorithm, the heuristic solution of each of 63 problems is compared with that of random scheduling. The result shows that the proposed heuristic algorithm provides better solution in light of the proposed cost function.

• Korean Management Science Review
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• v.13 no.1
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• pp.13-27
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• 1996

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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.59-65
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• 1999

This paper considers the cell formation in a manufacturing environment where the setup times and costs are significantly dependent on the sequence. The trade-off between saving on the setup costs and additional investment on new machines is considered for determining the economic number of cells. Accordingly, This paper develops a mixed integer program and mentions a variety of manufacturing situations where this model can be useful. This paper also includes an illustrative example.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.1-12
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• 2012

In this paper, we report a case study on the common due-date assignment and scheduling problem in a paper remanufacturing system that produces corrugated cardboards using collected waste papers for a given set of orders under the make-to-order (MTO) environment. Since the system produces corrugated cardboards in an integrated process and has sequence-dependent setups, the problem considered here can be regarded as common due-date assignment and sequencing on a single machine with sequence-dependent setup times. The objective is to minimize the sum of the penalties associated with due-date assignment, earliness, and tardiness. In the study, the earliness and tardiness penalties were obtained from inventory holding and backorder costs, respectively. To solve the problem, we adopted two types of algorithms: (a) branch and bound algorithm that gives the optimal solutions; and (b) heuristic algorithms. Computational experiments were done on the data generated from the case and the results show that both types of algorithms work well for the case data. In particular, the branch and bound algorithm gave the optimal solutions quickly. However, it is recommended to use the heuristic algorithms for large-sized instances, especially when the solution time is very critical.