• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.373-381
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• 2006

This paper considers a scheduling problem for a hybrid flowshop with dynamic order arrival. A hybrid flowshop is an extended form of a flowshop, which has serial stages like a flowshop but there can be more than one machine at each stage. In this paper, we propose a new method for the problem of scheduling with the objective of minimizing mean tardiness of orders which arrive at the shop dynamically. The proposed method is based on the list scheduling approach, however we use a more sophisticated method to prioritize lots unlike dispatching rule-based methods. To evaluate the performance of the proposed method, a simulation model of a hybrid flowshop-type production system is constructed. We implement well-known dispatching rules and the proposed methods in the simulation model. From a series of simulation tests, we show that the proposed methods perform better than other methods.

• Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.295-311
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• 2016

This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO) as a resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study and statistical analysis were performed to select the most adapted one for this problem. Then, the swarm behavior is tested for solving a combinatorial optimization problem such as a sequencing problem under constraints. Finally, an iterated local search algorithm based on probabilistic perturbation is sequentially introduced to the particle swarm optimization algorithm for improving the quality of solution. The computational results show that our approach is able to improve several best known solutions of the literature. In fact, 76 solutions among 120 were improved. Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements. Also, the performance of the proposed approach is evaluated according to a real-world industrial problem.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.254-265
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• 1999

We consider two stage hybrid flowshop scheduling problem when there are two non-identical parallel machines at the first stage, and only one machine at the second stage. Several well-known sequence-first allocate-second heuristics are considered first. We then propose an allocate-first sequence-second heuristic to find minimum makespan schedule. The effectiveness of the proposed heuristic algorithm in finding a minimum makespan schedule is empirically evaluated by comparing with easily computable lower bound. The proposed heuristic algorithm as well as the existing heuristics are evaluated by simulation in four cases which have different processing time distribution, and it is found that the proposed algorithm is more effective in every case.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.94-102
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• 2007

In this paper, we consider a line balancing problem in hybrid flowshops where each workstation has identical parallel machines. The number of machines in each workstation is determined in ways of satisfying pre-specified throughput rate of the system. To minimize the total number of machines in the systems, we propose five heuristic methods and one simulated annealing method. Extensive computational experiments found the superiorities of two heuristic methods and the meta-heuristic.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.1-10
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• 2011

In this study, we consider a capacity planning problem where the number of machines at each workstation is determined in manufacturing systems of top-edge electronic products such as semiconductor or display. The considered manufacturing system is the typical hybrid flowshop which has identical parallel machines at each workstation and the setup operation occurs when the types of consecutively processed products are different. The objective of the problem is finding good combinations of the numbers of machines at all workstations, under the given capital amount for purchasing machines. Various heuristic methods for determining the numbers of machines at workstations are proposed and the performances were tested through a series of computational experiments. In the study, a simulation model has been developed in order to simulate the considered manufacturing system with dynamic orders and complex process. The simulation model is also used for conducting the computational comparison test among various proposed methods.

• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.45-52
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• 2016

In this study, we consider a capacity planning problem of reentrant hybrid flowshops. High-tech electronic products such as semiconductor or TFT-LCD, are produced from manufacturing systems which can be considered as reentrant hybrid flowshops. In the considered capacity planning problem, we determine the number of machines at each stage in the manufacturing system. We introduce criteria indicating which stage needs additional machines or which stage needs reduction of machines considering the characteristics of the product types and the manufacturing system. The objective function of the problem is maximizing throughput rate of the system, of which values are obtained from the simulation model depicting the hybrid flowshops. The performance of the proposed methods were evaluated through a series of computational experiments. The simulation model was also used for conducting the comparison experiments among the proposed method and benchmarks.