• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.251-260
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• 1998

This paper deals with a simulated annealing neural network model for determining sequences of models inputted into a mixed model assembly line. We first present a energy function fitting to our problem, next determine the value of the parameters of the energy function using convergence ratio and the number of searched feasible solution. Finally we compare our model NMS with the modified Thomopoulos model. The result of the comparison shows that NMS and Thomopoulos offer a similar output in the problems having good smoothness.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.737-740
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• 1996

This paper suggests a boltzman machine neural network model to determine model input sequences in line balancing process of mixed model assembly line. We first present a proper energy function, next determine the value of parameters using simulation process.

• 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 Institute of Industrial Engineers
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• v.20 no.3
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• pp.15-34
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• 1994

This paper considers the genetic algorithms(GAs) for the mixed model assembly line sequencing(MMALS) in which the objective is to minimize the overall line length. To apply the GAs to the MMALS, the representation, selection, genetic sequencing operators, and genetic parameters are studied. Especially, the existing sequencing binary operators such as partially map crossover(PMX), cycle crossover(CX), and order crossover (OX) are modified to be suitable for the MMALS, and a new sequencing binary operator called immediate successor relationship crossover (ISR) is introduced. These binary operators mentioned above and/or unary operators such as swap, insertion, inversion, displacement, and splice are compared to find operators which work well in the MMALS. Experimental results indicate that 1) among the binary operators ISR operator is the best, followed by the modified OX, and the modified PMX, with the modified CX being the worst, 2) among the unary operators inversion operator is the best, followed by displacement, swap, and insertion, with splice being the worst, and 3) in general, the unary operators perform better than the binary operators for the MMALS.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.1-16
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• 1997

This paper improves the autonomy for supplier's schedule and the flexibility of the final assembly line. The final assembly line is a single work station and each product taking different assembly time is considered. In the assembly schedule, the heuristic method based on the goal chasing method is used. Consequently, suppliers can independently determine their output rates and thus, change their workload pattern according to their needs and priorities. Moreover, this flexibility can help to avoid expensive final-assembly-line stoppages in case of sudden part supply disruptions. The sequencing method can be easily implemented into an existing just-in-time system. In addition, the mathematical model was formulated and the algorithm was explained through the flow chart. The numerical example was given and the efficiency of this method is shown through the analysis of computational results of that example.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.647-647
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• 1994

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.224-231
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• 1994

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.310-320
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• 1999

A mixed model assembly line (MMAL) is a special type of production line where a variety of product models similar in product characteristics are assembled. Determining the model sequence is an important problem for the efficient use of MMALs. This paper considers interactive multiobjective decision making problems for MMAL sequencing. Evolution program is employed as an underlying framework. In this study, a way of approximating the linear utility function is first studied. To improve its search efficiency to the solution space preferred by a decision maker, some modifications of a standard evolution program are made: operating several subpopulations instead of a single population and merging two or more subpopulations to a single subpopulation, and using a Pareto pool. Extensive computational experiments are carried out to verify the performance of the proposed approach. The computational results show that our approach is promising in solution quality.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.523-534
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

• Journal of the Korea Safety Management & Science
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• v.7 no.3
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• pp.85-96
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.