• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.258-261
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• 2003

The purpose of this study is designing intelligent supplier management system with selected criteria for monitoring and evaluating suppliers by the information As suppliers keep changing their performance continuously according to the environment and with the passage or time. Companies need to monitor suppliers' condition continuously and choose the suitable action. This study considers a framework or supply chain management system usuig neural networks for ongoing partnership with criteria of supplier performance. The intelligent supplier management system that this study suggests ran offer the supplier evaluation criteria for monitoring and more efficient supply chain management ran be expected for cost reduction or supply chain management with this system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.115-119
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• 1996

고객의 수요가 매우 다양해지고 제조산업에서의 인건비 비중이 더욱 높아짐에 따라 기존의 생산 시스템은 새로운 변화를 요구하고 있다. 소품종 대량생산 시스템이나 유연생산 시스템 등을 위해 개발되어 온 대부분의 생산 계획은 off-line 상에서 시스템의 모든 요소들이 정상적이라는 가정하에서 수립되었다. 이로 인해서 기계가 갑작스럽게 정지하거나 공구의 이상 현상 등이 발생하여 기 수립된 계획에 따라 작업을 지속하기 힘든 경우가 생길 수 있다. 다양해지는 고객의 요구를 만족시키기 위하여 생산 시스템은 제어 측면에서 고기능화 되어가고 있다. 따라서 이러한 생산시스템의 운영을 위해 적절한 기법이 필요하게 되었다. 본 연구에서는 홀로닉 생산 시스템에 적용 가능한 스케쥴링 기법을 제시한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.179-186
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• 2006

There was a lot of research to integration of the transshipment and inventory problem in supply chain. Such a integration of inventory and transshipment problem called IRP (Inventory Routing Problem). We consider a distribution problem in which a set of products has to be shipped from a supplier to several retailers in a given planning horizon. Transshipment from the supplier to the retailer is performed by vehicles of limited capacity. Each retailer determines replenishment leadtime and order quantity with buffer management. A supplier determines optimal vehicle routing in supply chain. We suggest a heuristic algorithm which be used TOC buffer management in a replenishment problem and a tabu search algorithm in VRP (Vehicle Routing Problem).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.159-166
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• 2006

The aim of synchronization of production and transportation planning in the supply chain is to increase the flexibility and to decrease various costs. The suggested model in this study synchronizes the timing to supply to a downstream manufacturer directly after production and to be consumed in a downstream manufacturer right after receipt. This model deals with the frequent delivery in small amount which is a new trend of the transportation not governed the economy of scale principle. Moreover, various types of transportation governed by the economy of scale principle or not are considered. Then, the two-phase mathematical model is suggested to obtain optimal job sequence and production quantity for each tasks. But, it is difficult to gain optimal solutions if there is a transportation governed by the economy of scale principle in the supply chain, or the size of the problem is increased. Thus, heuristic algorithms based on simulated annealing and genetic algorithm are suggested to find good solutions in the reasonable time.

• Journal of the Korea Society for Simulation
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• v.9 no.1
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• pp.93-108
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• 2000

The stochastic manufacturing system has one or more random variables as inputs that lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of the system. These estimates could greatly differ from the corresponding real characteristics for the system. Multiple replications are necessary to get reliable information on the system and output data should be analyzed to get optimal solution. It requires too much computation time practically, In this paper a GA method, named Stochastic Genetic Algorithm(SGA) is proposed and tested to find the optimal solution fast and efficiently by reducing the number of replications.

• IE interfaces
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• v.4 no.2
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• pp.25-34
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• 1991

The problem of scheduling the passage things with low transit priority to maximize the amonnt that can be sent during given time periods without interfering with the fixed schedule for passage things with high transit priority in a track, is treated in this paper. The problem is transformed into the Time Expanded Network without traverse time through the Ford and Fulkerson Model and the Enumeration Algorithm is developed for solutions using TENET GENerator(TENETGEN). Finally, the proposed algorithm is compared with Dinic's maximal-flow algorithm and examined for the availability of the procedures on the personal computer.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.39-54
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• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.210-218
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• 2005

In the current global business environment, it is very important how to allocate products from the producer to buyers (or distributors). Sometimes some buyers can order more than pertinent demand due to inappropriate forecasting customers' orders. This is the big obstacle to the efficient allocation of products. If the producer can become aware of buyers' pertinent demand, it is possible to realize the high-level order fulfillment through the effective allocation of products. In this study, a new allocation policy is proposed considering buyers' demands. The backpropagation algorithm, one of algorithms in neural network theory, is used to find pertinent demands from the distributors' orders. In the experiment, an allocation policy considering buyers' demands outperforms previous allocation policies.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.75-94
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• 1998

AS/RS(Automated Storage/Retrieval Systems) has inflexibility in change after implementation and its initial cost is very high. Therefore, the proper and correct design of AS/RS is needed at the planning stage. Cost and performance are one of the most important factors in AS/RS design. There is a trade-off relationship between them. Velocity and number of stacker cranes have a deep relationship with performance of AS/RS. In this study, a model and a heuristic algorithm for finding optimal rack volumes and velocities of stacker for design of AS/RS are proposed with a numerical example.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.182-199
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• 1996

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involve so complicated and stochastic conditions such as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method and the savings method in terms of total logistics cost and driving time. This heuristic algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.