• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2187-2195
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• 2017

In order to solve the AC optimal power flow (OPF) problem considering the generators' on/off status, it is necessary to model the problem as mixed-integer nonlinear programming (MINLP). Because the computation time to find the optimal solution to the mixed-integer AC OPF problem increases significantly as the system becomes larger, most of the existing solutions simplify the problem either by deciding the on/off status of generators using a separate unit commitment algorithm or by ignoring the minimum output of the generators. Even though this kind of simplification may make the overall computation time tractable, the results can be significantly erroneous. This paper proposes a novel algorithm for the mixed-integer AC OPF problem, which can provide a near-optimal solution quickly and efficiently. The proposed method is based on a combination of the outer approximation method and the relaxed AC OPF theory. The method is applied to a real-scale power system that has 457 generators and 2132 buses, and the result is compared to the branch-and-bound (B&B) method and the genetic algorithm. The results of the proposed method are almost identical to those of the compared methods, but computation time is significantly shorter.

• International Journal of Highway Engineering
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• v.19 no.3
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• pp.65-70
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• 2017

PURPOSES : Pavement Management System contains the data that describe the condition of the road. Under limited budget, the data can be utilized for efficient plans. The objective of this research is to develop a mixed integer program model that maximizes remaining durable years (or Lane-Kilometer-Years) in road maintenance planning. METHODS : An optimization model based on a mixed integer program is developed. The model selects a cluster of sectors that are adjacent to each other according to the road condition. The model also considers constraints required by the Seoul Metropolitan Facilities Management Corporation. They select two lanes at most not to block the traffic and limit the number of sectors for one-time construction to finish the work in given time. We incorporate variable cost constraints. As the model selects more sectors, the unit cost of the construction becomes smaller. The optimal choice of the number of sectors is implemented using piecewise linear constraints. RESULTS : Data (SPI) collected from Pavement Management System managed by Seoul Metropolitan City are fed into the model. Based on the data and the model, the optimal maintenance plans are established. Some of the optimal plans cannot be generated directly in existing heuristic approach or by human intuition. CONCLUSIONS:The mathematical model using actual data generates the optimal maintenance plans.

• Korean Management Science Review
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• v.32 no.4
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• pp.109-133
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• 2015

This paper considers the allocation and engagement scheduling of air defense missiles by using MIP (mixed integer programming). Specifically, it focuses on developing a realistic MIP model for a real battle situation where multiple enemy missiles are headed toward valuable defended assets and there exist multiple air defense missiles to counteract the threats. In addition to the conventional objective such as the minimization of surviving target value, the maximization of total intercept altitude is introduced as a new objective. The intercept altitude of incoming missiles is important in order to minimize damages from debris of the intercepted missiles and moreover it can be critical if the enemy warhead contains an atomic or chemical bomb. The concept of so called the time window is used to model the engagement situation and a continuous time is assumed for flying times of the both missiles. Lastly, the model is extended to simulate the situation where the guidance radar, which guides a defense missile to its target, has the maximum guidance capacity. The initial mathematical model developed contains several non-linear constraints and a non-linear objective function. Hence, the linearization of those terms is performed before it is solved by a commercially available software. Then to thoroughly examine the MIP model, the model is empirically evaluated with several test problems. Specifically, the models with different objective functions are compared and several battle scenarios are generated to evaluate performance of the models including the extended one. The results indicate that the new model consistently presents better and more realistic results than the compared models.

• Journal of the Korean Institute of Gas
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• v.6 no.1 s.17
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• pp.86-91
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• 2002

This study introduces a method that selects equipments, so as to reach the reliability level, carrying out an optimization analysis which considers the reliability data and cost of the equipments. A more practical optimization problem has been formed using the object function based on the discrete function and the constraints. The jacked reactor being the subject, an optimization analysis was performed on equipments that have different failure rates depending on costs in order to reach the target reliability level required by the system. The mixed-integer programming (MIP) was used for this optimization analysis. When the jacked reactors target level of reliability was $1.65{\times}10^{-4}$, the result of the analysis showed the equipments with high cost and low failure rate were selected. However when the target level of reliability was low, the result showed that by choosing the equipments with lower cost and reliability over the more expensive one, the desired target level could be reached.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.365-372
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• 2021

This paper deals with an optimal Weapon-Target Assignment (WTA) algorithm for Closed-In Weapon Systems (CIWS), considering variable burst time. In this study, the WTA problem for CIWS is formulated based on Mixed Integer Linear Programming (MILP). Unlike the previous study assuming that the burst time is fixed regardless of the engagement range, the proposed method utilizes the variable burst time based on the kill probability according to the engagement range. Thus, the proposed method can reflect a more realistic engagement situation and reduce the reaction time of CIWS against targets, compared to the existing method. In this paper, we first reformulate the existing MILP-based WTA problem to accommodate the variable burst Time. The proposed method is then validated through numerical simulations with the help of a commercial optimization tool.

• 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 KIISE:Software and Applications
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• v.34 no.5
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• pp.431-446
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• 2007

Executable composite Web services are selected by binding a given abstract workflow with the specific Web services that satisfy given QoS requirements. Considering the rapidly increasing number of Web services and their highly dynamic QoS environment, the fast selection of composite services is important. This paper presents a method for quality driven comosite Web services selection based on a workflow partition strategy. The proposed method partitions an abstract workflow into two sub-workflows to decrease the number of candidate services that should be considered. The QoS requirement is also decomposed for each partitioned workflow. Since the decomposition of a QoS requirement is based on heuristics, the selection might fail to find composite Web services. To avoid such a failure, the tightness of a QoS requirement is defined and a workflow is determined to be partitioned according to the tightness. A mixed integer linear programming is utilized for the efficient service selection. Experimental results show that the success rate of partitioning is above 99%. Particularly, the proposed method performs faster and selects composite services whose qualities are not significantly different (less than 5%) from the optimal one.

• Journal of the Korean Society for Railway
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• v.8 no.4
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• pp.314-320
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• 2005

This paper is designed to help train dispatcher resolve railway conflicts in rent-time. We developed a mixed integer programming model to optimize the train schedule that determines the best overtaking or crossing positions, The objective of the model is to minimize the maximum lateness of the trains and reduce the total sum of the lateness, while satisfying the field constraints associated with the difference between passenger trains and freight trains, and the limited number of sidings. We applied the model on a portion of a single line track, Joong-Ang Line to ascertain the efficiency of the model, and showed how the model can be used to resolve the railway conflicts. The results indicates that our model can provide useful results in terms of optimal schedule for the test problem. This type of modeling approach would be useful for a train dispatcher to make a real-time railway conflict resolution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.85-92
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• 2018

Reductions of the electricity charge are achieved by demand management of the load. The demand management method of the load using ESS involves peak shifting, which shifts from a high demand time to low demand time. By shifting the load, the peak load can be lowered and the energy charge can be saved. Electricity charges consist of the energy charge and the basic charge per contracted capacity. The energy charge and peak load are minimized by Linear Programming (LP) and Quadratic Programming (QP), respectively. On the other hand, each optimization method has its advantages and disadvantages. First, the LP cannot separate the efficiency of the ESS. To solve these problems, the charge and discharge efficiency of the ESS was separated by Mixed Integer Linear Programming (MILP). Nevertheless, both methods have the disadvantages that they must assume the reduction ratio of peak load. Therefore, QP was used to solve this problem. The next step was to optimize the formula combination of QP and LP to minimize the electricity charge. On the other hand, these two methods have disadvantages in that the charge and discharge efficiency of the ESS cannot be separated. This paper proposes an optimization method according to the situation by analyzing quantitatively the advantages and disadvantages of each optimization method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.127-133
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• 2006

Minimizing the total number of setup changes of a machine increases the throughput and improves the stability of a production process, and as a result enhances the product quality. In this context, we consider a new product-mix problem that minimizes the total number of setup changes while producing the required quantities of a product over a given planning horizon. For this problem, we develop a mixed integer programming model. Also, we develop an efficient heuristic algorithm to find a feasible solution of good quality within reasonable time bounds. Computational results show that the developed heuristic algorithm finds a feasible solution as good as the optimal solution in most test problems. Also, we developed a web based scheduling and monitoring system for a zinc alloy production process using the developed heuristic algorithm. By using this system, we could find a monthly zinc alloy production schedule that significantly reduces the total number of setup changes.