• 대한산업공학회지
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• 제25권3호
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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.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 춘계학술대회
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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.

• 대한안전경영과학회지
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• 제7권3호
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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.

• 대한산업공학회지
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• 제25권4호
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• pp.411-420
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• 1999

A mixed model production line is a production line where a variety of product models are produced. In U-shaped production lines (called U-lines) used in just-in-time production system, the strategy of mixing product models is often used to provide various types of products to customers in time. Line balancing and model sequencing problems are important for an efficient use of mixed model U-lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. To promote diversity and search efficiency, in this paper the evolutionary system is based on the localized interactions within and between populations. Methods of selecting environmental individuals and evaluating fitness are developed. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm is superior to existing approaches.

• 한국경영과학회지
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• 제13권1호
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• pp.13-13
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• 1988

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.

• 대한산업공학회지
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• 제22권4호
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• pp.533-549
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• 1996

This paper is concerned with a sequencing problem in mixed model assembly lines, which is important to efficient utilization of the lines. In the problem, we deal with the two objectives of minimizing the risk of stoppage and leveling part usage, and consider sequence-dependent setup time. In this paper, we present a genetic algorithm(GA) suitable for the multi-objective optimization problem. The aim of multi-objective optimization problems is to find all possible non-dominated solutions. The proposed algorithm is compared with existing multi-objective GAs such as vector evaluated GA, Pareto GA, and niched Pareto GA. The results show that our algorithm outperforms the compared algorithms in finding good solutions and diverse non-dominated solutions.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 1999년도 춘계공동학술대회:정보화시대의 지식경영
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• pp.34-35
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• 1999

• 산업경영시스템학회지
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• 제12권19호
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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.

• 경영과학
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• 제11권1호
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• pp.91-106
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• 1994

In mixed model assembly lines, products are assembled seqeuntially that have different combination of options specified by customers. In just in time (JIT) environment, production smoothing becomes an important issue for sub-lines which supply the necessary parts to each workstation of the assembly line. Another important issue is to avoid line stopping caused by work overload in workstations. To find a sequence which minimizes the costs associated with line stoppage and the option parts inventory level, a nonlinear mixed integer programming is formulated. Recognizing the limit of the Branch and Bound technique in large sized problems, a heuristic solution procedure is proposed. The performance of the heuristic is compared with the Branch and Bound technique through randomly generated test problems. The computational results indicate that on the average the heuristic solutions deviate approximately 3.6% from the optimal solutions.

• 산업경영시스템학회지
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• 제20권43호
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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.