• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.381-385
• /
• 2003

We consider the bandwidth parking problem arising from telecommunication networks The problem is to determine the set of calls to be routed and an assignment or them to the paths in arc capacitated network. The objective is to maximize profit. We formulate the problem as an integer programming and propose an algorithm to solve it. Column generation technique to solve the linear programming relxation is proposed with two types of columns in addition, to obtain an optimum integer solution, we consider a new branching strategy. Computational experiments show that the algorithm gives option at solutions within reasonably small time limits.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.19 no.38
• /
• pp.9-15
• /
• 1996

The purpose of this research is to develop a method for part-machine grouping subject to production and management constraints. In the proposed integer programming model, minimization of operating and material-handling costs are considered as an objective function. The model allows one to recognize the existing parts and machines into disaggregated cells. New constraints are introduced in the model to resolve unbalancing capacity and bottleneck problems. It is found that this approach could have a better flexibility on cell size design for mote alternatives than conventional methods. Experimental grouping and comparison studies with ROC algorithm are given for evaluation purposes.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.7
• /
• pp.1125-1129
• /
• 2015

Increasing peak load is one of the major concerns about operation of urban railroad systems. Since ESSs (Energy Storage Systems) have a great potential for shaving the peak load, there has been a growing interest in the use of ESS for peak load reduction. Also, ESS can be optimally scheduled to minimize the electricity purchasing cost under a given ToU (Time-of-Use) tariff by taking advantage of electricity price difference between peak and off-peak time. This paper presents a Mixed Integer Programming (MIP)-based ESS scheduling method to minimize the electricity purchasing cost under a ToU tariff for an urban railroad system.

• Journal of Korean Institute of Industrial Engineers
• /
• v.32 no.2
• /
• pp.74-81
• /
• 2006

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new $l_1$-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number of discriminant functions as an input, the proposed model considers the synergy as well as the individual role of the functions involved and implements a simplest nonlinear decision surface that best separates the data on hand. Hence, exploiting powerful MILP solvers, the model efficiently analyzes any given data set for its piecewise nonlinear separability. The classification of four sets of artificial data demonstrates the aforementioned strength of the proposed model. Classification results on five machine learning benchmark databases prove that the data separation via the proposed MILP model is an effective supervised learning methodology that compares quite favorably to well-established learning methodologies.

• Management Science and Financial Engineering
• /
• v.17 no.2
• /
• pp.1-21
• /
• 2011

This paper considers an integrated inventory-distribution system with a fleet of heterogeneous vehicles employed where a single warehouse distributes a single type of products to many spatially distributed retailers to satisfy their dynamic demands. The problem is to determine order planning at the warehouse, and also vehicle schedules and delivery quantities for the retailers with the objective of minimizing the sum of ordering cost at the warehouse, inventory holding cost at both the warehouse and retailers, and transportation cost. For the problem, we give a Mixed Integer Programming formulation and develop a Lagrangean heuristic procedure for computing lower and upper bounds on the optimal solution value. The Lagrangean dual problem of finding the best Lagrangrean lower bound is solved by subgradient optimization. Computational experiments on randomly generated test problems showed that the suggested algorithm gives relatively good solutions in a reasonable amount of computation time.

• Management Science and Financial Engineering
• /
• v.11 no.1
• /
• pp.49-61
• /
• 2005

We consider the graph disconnection problem, which is to find a set of edges such that the total cost of destroying the edges is no more than a given budget and the weight of nodes disconnected from a designated source by destroying the edges is maximized. The problem is known to be NP-hard. We present an integer programming formulation for the problem and develop an algorithm that includes a preprocessing procedure for reducing the problem size, a heuristic for providing a lower bound, and a cutting plane algorithm for obtaining an upper bound. Computational results for evaluating the performance of the proposed algorithm are also presented.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.29 no.1
• /
• pp.113-125
• /
• 2004

The network disconnection problem ms to find a set of edges such that the total cost of removing the edges is no more than a given budget and the weight of nodes disconnected from a designated source by removing edges is maximized. Martel et at. have shown that the problem with unit capacity and unit demand Is NP-hard and Myung and kim present an integer programming formulation and develop an algorithm that Includes a preprocessing procedure and lower and upper bounding strateagies. in this paper, we present new findings on the properties of the optimal solution and an alternative integer programming formulation, based on which new lower and upper bounding strategies are developed. Computational results for evaluating the performance of the proposed algorithm are also presented.

• Journal of the military operations research society of Korea
• /
• v.30 no.2
• /
• pp.133-140
• /
• 2004

In this paper, with the limited range of ammunition supply point(ASP) at ammunition battalion in specific corps and light automobile battalion(LAB) directly supports its vehicle for ammunition supply, we propose optimal model to minimize transportation time and logistics cost using integer programming(IP) for efficient ammunition resupply allocation during a given operation period of front combat unit. And then, we consider ammunition treatment and supply capacity of ammunition supply point(ASP), constraint elements of transportation ability considering time and cost, ammunition storage capacity of combat unit, combat situation and unit mission to propose this model. Finally, through numerical example, we examine the applicable feasibility of proposed model.

• Korean Journal of Community Nutrition
• /
• v.12 no.5
• /
• pp.630-638
• /
• 2007

The purpose of this study is to investigate an efficient use of labor in personnel scheduling for the restaurant industry. More specifically, this study attends to reduce overall labor cost while not sacrificing both full-time and part-time employees' schedules. The customers' demands were measured by sales in this analysis. Historically, server scheduling in the restaurant has been practiced by manager's experience and intuition; however, those practices provided drawbacks because managers often fail to consider external factors such as a employees' working conditions and change in a restaurant's size. The result of a new method in personnel scheduling provided significant cost saving compared to a previous scheduling technique. This study found that a new method in personnel scheduling allowed the restaurant to save labor cost. The outcome of this study should of for important strategic implication for the restaurant managers.

• Journal of Communications and Networks
• /
• v.17 no.5
• /
• pp.473-481
• /
• 2015

In this study, we propose a clustering algorithm to enhance the performance of wireless sensor and actuator networks (WSANs). In each cluster, a multi-level hierarchical structure can be applied to reduce energy consumption. In addition to the cluster head, some nodes can be selected as intermediate nodes (INs). Each IN manages a subcluster that includes its neighbors. INs aggregate data from members in its subcluster, then send them to the cluster head. The selection of intermediate nodes aiming to optimize energy consumption can be considered high computational complexity mixed-integer linear programming. Therefore, a heuristic lowest energy path searching algorithm is proposed to reduce computational time. Moreover, a channel assignment scheme for subclusters is proposed to minimize interference between neighboring subclusters, thereby increasing aggregated throughput. Simulation results confirm that the proposed scheme can prolong network lifetime in WSANs.