• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.155-164
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• 1996

Biomass to methane via anaerobic digestion conversion is a good supply method of substitutable energy resources. The economic viability of this technology is contingent upon managing the production facilities in a cost effective manner. The problem is to determine the batch production sequence as well as the batch residence times in the digester so as to maximize total gas production over a given planning horizon. The problem is difficult to solve since the batch sequencing decisions and the batch residence time decisions cannot be isolated. This paper developes a heuristic algorithm which is based on a dynamic programming procedure for the multiple feedstock sequencing and scheduling biogas production systems and demonstrates to yield good results.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.309-314
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• 2007

Optimal layer sequencing of a multi-layered acoustical foam is solved to maximize its sound transmission loss. A foam consisting of air and poroelastic layers can be optimized when a limited amount of a poroelastic material is allowed. By formulating the sound transmission loss maximization problem as a one dimensional topology optimization problem, optimal layer sequencing and thickness were systematically found for several frequencies. For optimization, the transmission losses of air and poroelastic layers were calculated by the transfer matrix derived from Biot's theory. By interpolating five intrinsic parameters among several poroelastic material parameters, dear air-poroelastic layer distributions were obtained; no filtering or post-processing was necessary. The optimized foam layouts by the proposed method were shown to differ depending on the frequency of interest.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.930-935
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• 2002

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problem are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed­model production lines, the two problems have been considered separately. In 1his research, an endosymbiotic evolutionary algorithm, which is a kind of evolutionary algorithm, is adopted as a methodology in order to solve the two problems simultaneously. Some evolutionary search capability, rapidity of convergence and population diversity. The proposed algorithm is compared with the existing evolutionary algorithm in terms of solution quality. The experimental results confirm the effectiveness of our approach.

• Journal of the Korea Safety Management & Science
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• v.5 no.1
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• pp.69-82
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• 2003

The sequence which minimizes overall utility work in car assembly lines reduces the cycle time, the number of utility workers, and the risk of conveyor stopping. This study suggests mathematical formulation of the sequencing problem to minimize overall utility work, and present a genetic algorithm which can provide a near optimal solution in real time. To apply a genetic algorithm to the sequencing problem in car assembly lines, the representation, selection methods, and genetic parameters are studied. Experiments are carried out to compare selection methods such as roullette wheel selection, tournament selection and ranking selection. Experimental results show that ranking selection method outperforms the others in solution quality, whereas tournament selection provides the best performance in computation time.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.95-105
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• 2002

This paper considers the sequencing of products in car assembly lines under Just-In-Time systems. Under Just-In-Time systems, the most important goal for the sequencing problem is to keep a constant rate of usage every part used by the systems. In this paper, tabu search technique for this problem is proposed. Tabu search is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality and computation time. Various examples are presented and 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.18 no.33
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• pp.29-37
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• 1995

An Automated Storage/Retrieval Systems(AS/RS) has been gradually emphasized because of the change of production and distribution environment. This paper develops algorithm and Shortest Distance Model that can reduce the traveling time of a stacker crane for efficient operation of AS/RS. In order to reduce the traveling time of a stacker crane, we determine the order processing and then the sequencing of storage/retrieval for each item. Order processing is determined based on the SPT(Shortest Processing Time) concept considering a criterion of retrieval coordinate. The sequencing of storage/retrieval is determined based on the Shortest Distance Model by using a modified SPP(Shortest Path Problem) of network problem. A numerical example is provided to illustrate the developed algorithm and Shortest Distance Model.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.115-125
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• 2004

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problems are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed-model production lines, the two problems have been considered separately. A genetic algorithm for balancing and sequencing in mixed-model U line is proposed. A presentation method and genetic operators are proposed. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that the proposed algorithm is promising in solution quality.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.11-18
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• 2016

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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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.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.425-436
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• 2006

The e-learning system in which the learning is carried out by predefined procedures cannot offer proper learning suitable to the capability of individual learner. To solve this problem, SCORM sequencing can be used to define various learning procedures according to the capabilities of learners. Currently the sequencing is designed by teachers or learning contents producers to regularize the learning program. However, the predefined sequencing may not reflect the characteristics of the learning group. If inappropriate sequencing is designed it may cause the unnecessary repetition of learning. In this paper, we propose an automated evaluation system in which dynamic sequencing is applied. The dynamic sequencing reflects the evaluation results to the standard scores used by sequencing. By changing the standard scores, the sequencing changes dynamically according to the evaluation results of a learning group. Through several experiments, we verified that the proposed learning system that uses the dynamic sequencing is effective for providing the proper learning procedures suitable to the capabilities of learners.