• 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 Institute of Industrial Engineers
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• v.33 no.3
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• pp.373-380
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• 2007

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over and overlapping as well as demand splitting are considered. Also, maximum number of setups for each time period is not limited. For this LSSP, we have formulated a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we have developed an efficient heuristic algorithm by combining decomposition scheme with local search procedure. Test results show that the developed heuristic algorithm finds good quality (in practice, even better) feasible solutions using far less computation time compared with the CPLEX, a competitive MIP solver.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1610-1616
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• 2013

Recently, district heating and cooling (DHC) systems based on combined cycle generation (CCG) providers are increasing in Korea. Since characteristics of combined heat and power (CHP) generators and heat demands of providers, heat trading between DHC providers based on the economic viewpoint is required; the heat trading has been doing. In this paper, a mathematical model for optimal operation based on heat trading between DHC providers is proposed. Especially, start-up characteristic of CCG is included. The operation model is established by mixed integer linear programming (MILP).

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.143-156
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• 2005

Facility location planning (FLP) problem is the strategic level planning in supply chain. The FLP is significantly affected by the operation time of each facility. In most of the FLP researches, operation time of facility has been treated as a fixed value. However, the operation time is not a static factor in real situations and the fixed operation time may lead unrealistic FLP. In this paper, a mixed integer programming (MIP) model is proposed for solving the 3-stage FLP problem and operation times are adjusted by the results from the simulation model and an iterative approach combining the analytic model and simulation model is proposed to obtain more realistic operation plans for FLP problems.

• Journal of the military operations research society of Korea
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• v.34 no.3
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• pp.1-12
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• 2008

Design of supply chain network (SCN) is required to optimize every factor in SCN and to provide a long-term and strategic decision-making. A mathematical model can not reflect the real world because design of SCN contains variables and stochastic factors according to status of its system. This paper presents the designing methodology of military SCN using the mathematical model and the simulation model. It constructs SCN to minimize its total costs using the Mixed Integer Programming (MIP) model. And we solve problems of a vehicle assignment and routing through adaptation of experiment parameters repeatedly in the simulation model based on the results from the MIP model. We implement each model with CPLEX and AutoMod, and experiment to reconstruct SCN when the Logistic Support Unit is restricted to support military units. The results from these experiments show that the proposed method can be used for a design of military SCN.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.311-321
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• 2005

A competitive generating company (GENCO) could maximize its payoff by optimizing its generation assets. This paper considers the GENCO's arbitrage problem using price-based unit commitment (PBUC). The GENCO could consider arbitrage opportunities in purchases from qualifying facilities (QFs) as well as simultaneous trades with spots markets for energy, ancillary services, emission, and fuel. Given forecasted hourly market prices for each market, the GENCO's generating asset arbitrage problem is formulated as a mixed integer program (MIP) and solved by a branch-and-cut algorithm. A GENCO with 54 thermal and 12 combined-cycle units is considered for analyzing the proposed formulation. The proposed case studies illustrate the significance of simultaneous arbitrage by applying PBUC to multi-commodity markets.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.99-108
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• 2001

A framework of using and integrating GIS and OR tools for determining the best site selection has been provided. In this research, we demonstrated that both the P-Median heuristic method and MIP method can be successfully applied to the optimum site selection problem of oil tank location selection. Furthermore, the results identified by both approaches are identical. To accomplish this, both GIS road and maritime networks have been constructed and combined to calculated the minimum distance matrix, which is required by both approaches. After the application to the Korean peninsula, the facility locations chosen are Kunsan, Yosu, Busan, and Okgye for each district. As has been shown, the power of GIS and both algorithm have been demonstrated throughout the research and further similar research can also be conducted using the power of GIS and Operations Research tools.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.744-761
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• 2016

For about the past decade and a half research efforts into cognitive radio networks (CRNs) have increased dramatically. This is because CRN is recognized as a technology that has the potential to squeeze the most out of the existing spectrum and hence virtually increase the effective capacity of a wireless communication system. The resulting increased capacity is still a limited resource and its optimal allocation is a critical requirement in order to realize its full benefits. Allocating these additional resources to the secondary users (SUs) in a CRN is an extremely challenging task and integer programming based optimization tools have to be employed to achieve the goals which include, among several aspects, increasing SUs throughput without interfering with the activities of primary users. The theory of the optimization tools that can be used for resource allocations (RA) in CRN have been well established in the literature; convex programming is one of them, in fact the major one. However when it comes to application and implementation, it is noticed that the practical problems do not fit exactly into the format of well established tools and researchers have to apply approximations of different forms to assist in the process. In this survey paper, the optimization tools that have been applied to RA in CRNs are reviewed. In some instances the limitations of techniques used are pointed out and creative tools developed by researchers to solve the problems are identified. Some ideas of tools to be considered by researchers are suggested, and direction for future research in this area in order to improve on the existing tools are presented.

• 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 the Korean Geographical Society
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• v.49 no.3
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• pp.423-437
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• 2014

Districting is a spatial decision making process to make a new regional framework for affecting human activities. Natural barriers such as rivers and mountains located within a reorganized district may reduce the efficiency of reorganized human activities. This implies that it is necessary to consider boundary characteristics in a districting process. The purpose of this research is to develop a new spatial optimization model based on boundary characteristics for districting problems. The boundary characteristics are evaluated as continuous value expressing the possibility of combining adjacent two basic spatial units rather than a dichotomous value with 1 or 0 and are defined as an objective function in the model. In addition, the model has explicitly formulated contiguity constraints as well as constraints enforcing demand balance among districts such as population and area. The boundary attributes are categorized into physical and relational characteristics. Suitability analysis is used to combine various variables related to each boundary characteristic and to evaluate the coupling possibility between two neighboring basic units. The model is applied to an administrative redistricting problem. The analytical results demonstrate that various boundary characteristics could be modeled in terms of mixed integer programming (MIP).