• IE interfaces
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• v.17 no.3
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• pp.282-293
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• 2004

Line Balancing is the problem to assign tasks to stations while satisfying some managerial viewpoints. Most researches about the Mixed-Model Line Balancing problems are focused on the minimizing the total processing time or the number of workstations. Independently, some research reports consider the balance issues of the physical workloads on the assembly line. In this paper, we are presenting a new mathematical model to accomplish the line balance considering both the processing time and the workloads at the same time. To this, end, we propose an zero-one integer program problem, and we use the Chebyshev Goal Programming approach as the solution method. Some computational test runs are performed to compare the pay-offs between the processing time and the workloads. And, the test results show us that the reliable balanced work schedules can be obtained through the proposed model.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.87-104
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• 2014

This paper proposes regionally centralized multistage reverse logistics (cmRL) networks and regionally decentralized multistage reverse logistics (dmRL) networks. cmRL considers whole area of RL network, while dmRL regionally distributed area of RL network. Each type is formulated by the mixed integer programming (MIP) models, which are realized in genetic algorithm (GA) approach. Two types of numerical experiments using RL network are presented and various measures of performance are used for comparing the efficiency of the cmRL and the dmRL. Finally, it is proved that the performance of the cmRL is superior to that of the dmRL.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2626-2646
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• 2014

This study presents a power and Physical Resource Blocks (PRBs) joint allocation algorithm to coordinate uplink (UL) interference in the device-to-device (D2D) underlaying Long Term Evolution-Advanced (LTE-A) networks. The objective is to find a mechanism to mitigate the UL interference between the two subsystems and maximize the weighted sum throughput as well. This optimization problem is formulated as a mixed integer nonlinear programming (MINLP) which is further decomposed into PRBs assignment and transmission power allocation. Specifically, the scenario of applying imperfect channel state information (CSI) is also taken into account in our study. Analysis reveals that the proposed PRBs allocation strategy is energy efficient and it suppresses the interference not only suffered by the LTE-A system but also to the D2D users. In another side, a low-complexity technique is proposed to obtain the optimal power allocation which resides in one of at most three feasible power vectors. Simulations show that the optimal power allocation combined with the proposed PRBs assignment achieves a higher weighted sum throughput as compared to traditional algorithms even when imperfect CSI is utilized.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.42-50
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• 2006

The multi-criteria group decision making (MCGDM) problem is to determine the best compromise solution in a set of competing alternatives that are evaluated under conflicting criteria by decision maker (DM)s. In this paper, we propose a mixed-integer programming (MIP) model to solve MCGDM. The existing method based on minimizing a distance measure such as Median Approach can not guarantee the best compromise solution because the element of median point vector is defined with respect to each criteria separately. However, by considering all criteria simultaneously, we generate median point that is better for locating the best compromise solution. We also utilize the concept of spatial dispersion index (SDI) to produce a threshold value, which is used as a guideline to choose either the Utopian Approach or the Median Approach. And we suggest using CBITP (Convex hull of individual maxima Based Interactive Tchebycheff Procedure) to provide DMs with various Pareto-optimal solutions so that DMs have broad range of selection.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.51-63
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• 1994

Many themes have been studied for FMS problems. But most researches have focused on specific themes; Machine selection, Loading, Routing, Machine layout, etc. So many decision makers who want to introduce FMS to his factory, have many problems, because they do not know either what size of FMS should be introduced or what amount of money should be invested. The objective of this research is to help the decision makers who want to introduce FMS. This research consists of three major part, first, Machine selection, second, Loading, and third, Machine Layout. In the first part of the research, machines are selected with minimum cost satisfying the given demand of each part. In the second part, each operations with its required tools are allocated to those machines. In the third part the locations of each selected machines are determined. And dissimilarity coefficients between each pair of machines are calculated as the measure of distance. With above three steps, we have selected machines, allocated operations to those machines, and the layout configuration of those machines. And for each three steps, Mixed Integer Programming models are formulated. In order to solve the large problems and reduce the computer execution time, three heuristic algorithms are developed for the three mixed integer programming models.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.382-392
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• 2006

Vendor-managed inventory policy(VMIP) is a supply-chain initiative where the supplier is authorized to manage inventories of items at retail locations. In VMIP, the supplier monitors sales and stock information at retail locations and makes decisions of inventory replenishment and transportation simultaneously. VMIP has been known as an effective supply chain strategy that can realize many of benefits obtainable only in a fully integrated supply chain. However, VMIP does not always lead to lower the supply chain cost. It sometimes generates the total supply chain cost higher than the traditional retailer-managed inventory policy (RMIP). In this paper, we perform a comparison study on RMIP and VMIP in the retail supply chain which consists of a single supplier and a number of retailers. We formulate mixed integer programming models for both RMIP and VMIP with vehicle routing problems and perform computational experiments on various test problems. Furthermore, we derive the conditions which guarantee the dominant position for VMIP with respect to total supply chain cost in the simple retail supply chain.

• The KIPS Transactions:PartC
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• v.14C no.2
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• pp.179-184
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• 2007

The problem of selecting base station location in the design of mobile communication system has been basically regarded as a problem of assigning maximum users in the cell to the minimum base stations while maintaining minimum SIR. and it is NP hard. The objective function of warehouse location problem, which has been used by many researchers, is not proper function in the base station location problem in CDMA mobile communication, The optimal and approximate solutions have been presented by using proposed object function and algorithms of exact solution, and the simulation results have been assessed and analyzed. The optimal and approximate solutions are found by using mixed integer programming instead of meta-heuristic search methods.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.57-66
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• 2012

The paper deals with the development of a model for group decision making under multiple criteria. The Multi-criteria group decision making (MCGDM) is the process to determine the best compromise solution in a set of competing alternatives that are evaluated by decision makers having their own preferences on conflicting objectives. For MCGDM, we propose a Mixed-Integer Programming (MIP) model that implements a revised median approach by noticing that the original median approach cannot consider the willingness to reject and the indifferent preference conditions. The proposed MIP model tries to select a common best Pareto-optimal solution by maximizing the overall desirability considering the willingness to reject and the indifferent preference that represent the tolerance measure of each decision maker. To evaluate the effectiveness of the proposed model, we compared the results of the proposed model with those of the median approach. The results showed that the proposed MIP model produces more realistic and better compromised alternative by incorporating the decision maker's willingness to reject and the indifferent preferences over each criteria.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.1018-1023
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• 2009

This paper describes a reduction in the peaks of traction energy for metro railways in timetabling. We develope a mixed integer programming (MIP) model, which minimizes the number of trains running simultaneously. We suggest two approaches. In the first approach, we use the commercial MIP solver, CPLEX. In the second approach, we propose a heuristic algorithm. We apply both methods to the current daily timetable of the Korea Metropolitan Subway. We determine an optimal solution, which results in an improvement of approximately 25% over the current timetable.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.40-48
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• 2009

In this article, scheduling of a casting sequence is studied in a casting foundry which must deliver products according to the Just-in-time(JIT) production policy of a customer. When a foundry manufactures a variety of casts with an identical alloy simultaneously, it frequently faces the task of production scheduling. An optimal casting schedule should be emphasized in order to maximize the production rate and raw material efficiency under the constraints of limited resources; melting furnaces and operation time for a casting machine. To solve this practical problem-fulfilling the objectives of casting the assigned mixed orders for the highest raw material efficiency in a way specified by the customer's JIT schedule, we implement simple integer programming. A simulation to solve a real production problem in a typical casting plant proves that the proposed method provides a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Employing this simple methodology, a casting foundry having an automated casting machine can produce a mixed order of casts with a maximum furnace utilization within the due date, and provide them according to their customer's JIT inventory policy.