• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.715-722
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• 2005

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used products while satisfying the demand of their parts or components over a planning horizon. The case of single product type with assembly structure is considered for the objective of minimizing the sum of disassembly operation and inventory holding costs. In particular, the resource capacity constraint is explicitly considered. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To show the performance of the heuristic, computational experiments are done on a number of randomly generated problems, and the test results show that the algorithm can give near optimal solutions within a very short amount of computation time.

• IE interfaces
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• v.16 no.4
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• pp.441-449
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• 2003

In this paper we propose a distribution planning method aiming the use in the real-life situations. The assumed form of the distribution network is arborescence. At every node in the distribution network, orders are placed periodically. At each renewal of planning horizon, demand informations of periods in the horizon are updated. The objective of the problem is to minimize the total cost, which is the sum of holding and backorder costs of all sites during planning horizon. For such a situation, this study addressed an effective distribution plan when demands for demand-sites are provided for a given planning horizon.

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.95-112
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• 2006

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts and/or components over a planning horizon. The case of assembly product structure is considered while the resource capacity constraints are explicitly considered. A cost-based objective is considered that minimizes the sum of disassembly operation and inventory holding costs. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To test the performance of the heuristic, computational experiments are done on randomly generated problems, and the results show that the heuristic gives near optimal solutions within a very short amount of computation time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.81-84
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• 2003

The ability to determine the optimal frequencies and offsets for independent and unrestricted ordering cycles for multiple items can be very valuable for managing storage capacity constrained facilities in a supply chain. The complexity of this problem has resulted in researchers focusing on more tractable surrogate problems that are special cases of the base problem. Murthy et al. (European Journal of Operation Research 2003) developed insights leading to solution of the original problem and present a heuristic for offsetting independent and unrestricted ordering cycles for items to minimize their joint storage requirements. However, their study cannot find optimal solution due to the Greedy Heuristic solution procedure. In this paper, we present a complete procedure to find the optimal solution for the model with a integer programming optimization approach and genetic algorithm. Numerical examples are included to compare each model with that of Murthy et at. Research of this type may prove useful in solving the more general problem of selecting order policies to minimize combined holding, ordering, and storage costs.

• IE interfaces
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• v.14 no.3
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• pp.255-262
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• 2001

Containerization of cargo transportation has been norm in the word wide maritime services, but containerized trades are typically unbalanced in terms of the number of inbound and outbound containers. Therefore it is critical for shipping companies to find operating policy such as the repositioning of empty containers or replenishing of short-term leasing containers from leasing companies to satisfy the freighter's demands of containers. This paper develops a simulation model using ARENA to establish shipping company's operational policy to relocate and replenish empty containers. Furthermore, this study proposes simple and heuristic empty container repositioning rules to minimize the relevant cost in terms of leasing, repositioning, and inventory holding costs.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.328-336
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• 2001

In this paper, an approach is presented for determining the required storage capacity of a warehouse with leased public space. Storage assignment policies considered are randomized and class-based storage assignment policies. An analytic model for each of the storage policies is formulated with the objective of minimizing the cost of owned storage space and leased space while satisfying a desired service level of protection against space shortages. Cost functions used in the models are piecewise liear with fixed costs. For the models, algorithms are developed to generate optimal solutions. The approach is applied to the systems where the standard economic-order-quantity inventory model is used for all items being stored in the warehouse.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.369-374
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• 2003

Disassembly scheduling is the problem or determining the ordering and disassembly schedules or used or end-of-life products while satisfying the demand or their parts or components over a certain planning horizon. To represent and optimally solve the basic case. i e ., single product type without parts commonality, an Integer programming model is suggested for the objective or minimizing the sum or purchase, setup, inventory holding, and disassembly operation costs. Then, the basic model is offended to consider the cases or single and multiple product types with parts commonality. Computational experiments done on the examples obtained from the literature show that the integer programming approach suggested in this paper works well.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.363-368
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• 2014

During the fierce competition among the companies, improvement of logistics center managing efficiency is importantly recognized. Among them, studies on improvement of picking work process on about 55% of logistics center managing costs are continuously conducted. And, most of studies focus on analysis on strengths and weaknesses of picking method performable on the stage of logistics center design, etc, so the purposes of this research are to define load location rule by product releasing frequency in logistics managing environment based on conveyer and suggest expected effects by simulation analyzing method to improve picking managing efficiency.

• IE interfaces
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• v.11 no.1
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• pp.23-32
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• 1998

This paper presents a model for assessing the efficiency of logistics activities in distribution centers. The DEA approach is adopted to compare the relative efficiency of distribution centers, where considered as input and output factors are warehouse floor area, field storage area, average inventory level, overhead costs, number of workers, number of orders, and total value of goods handled. The artificial neural network approach is also adopted to overcome the limitation of DEA. The 12 distribution centers of Korea Telecom are studied for the validation of the model, which results in 84.9% of learning accuracy. This model can be used to identify the inefficient factors in a distribution center and to reveal changes in the degree of efficiency over time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.100-110
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• 1990

An optimal raw mix model in stainless steel making is developed. The key raw materials in stainless steel making are stainless steel scrap, steel scrap, and alloy materials like Fe-Ni, Fe-Cr. Among those raw materials, the alloy metals are very expensive as well as rapidly price-changing items. Consequently, it is very important to develop an minimal cost raw mix scheme while the produced stainless steel satisfies the required specification in it's composition. The linear programming model is employed to determine the minimal cost raw mix scheme. Compared with the method being used, the developed linear programming model gives much faster and better solution (lower cost raw mix plan). Together with the linear programming model, the database is also developed, which includes the following: 1) data for raw materials, such as compositions, costs, densities, available inventory levels, and so on, 2) the required specifications process. The developed optimal raw mix model will be implemented in VAX computer.