• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.102-106
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• 2004

The purpose of this paper is to develope a large-scale mixed integer program MIPBB. In this paper, the various issues such as branching strategies, searching and bounding strategies, storing basis information, handling numerical instability, that are important for developing a large-scale mixed integer programming program, are considered. And the experimental results of MIPBB are presented and compared to those of GLPK.

• 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.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.246-252
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• 2010

A binary linear integer program is formulated for the problem of expanding the capacity of a fiber optic network and routing the traffic to deliver new interactive multimedia services. A two-phase Lagrangian dual search procedure and a Lagrangian heuristic are developed. Computational results show superior performance of the two-phase subgradient optimization compared with the conventional one-phase approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.50-55
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• 2004

We propose an intgrated Gill environment system having only integer fuzzy operations in the consequent part and the defuzzification stage. In this paper, we also propose an integrated Gill environment system with 4 parallel fuzzy processing units to be operated in parallel on the classification of the sensed image data. In this, we solve the problems of taking longer times as the fuzzy real computations of [0, 1] by using the integer pixel conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. This procedure is performed automatically in the GUI application program. As a Gill environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be operated in parallel manner for MIMO or MISO systems.

• IE interfaces
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• v.24 no.2
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• pp.151-155
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• 2011

In this study, we propose a signomial classification method with ₀-regularization (₀-)which seeks a sparse signomial function by solving a mixed-integer program to minimize the weighted sum of the ₀-norm of the coefficient vector of the resulting function and the $L_1$-norm of loss caused by the function. $SC_0$ gives an explicit description of the resulting function with a small number of terms in the original input space, which can be used for prediction purposes as well as interpretation purposes. We present a practical implementation of $SC_0$ based on the mixed-integer programming and the column generation procedure previously proposed for the signomial classification method with $SL_1$-regularization. Computational study shows that $SC_0$ gives competitive performance compared to other widely used learning methods for classification.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.311-314
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• 2005

Supply chain optimization is one of the most important components in the optimization of a company's value chain. This paper considers the problem of designing the supply chain for a product that is represented as an assembly bill of material (BOM). In this problem we are required to identify the locations at which different components of the product arc are produced/assembled. The objective is to minimize the overall cost, which comprises production, inventory holding and transportation costs. We assume that production locations are known and that the inventory policy is a base stock policy. We first formulate the problem as a 0-1 nonlinear integer programming model and show that it can be reformulated as a 0-1 linear integer programming model with an exponential number of decision variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.1
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• pp.89-95
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• 2006

Planning distributed manufacturing logistics is one of main issues in supply chain management. This paper proposes a hybrid heuristic approach for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network. MLCLSP corresponds to a mixed integer programming (MIP) problem. With integer variable solutions determined by heuristic search, this MIP problem becomes linear program (LP). By repeatedly solving the relaxed MIP problems with a heuristic search method in a hybrid manner, this proposed approach allocates finite manufacturing resources fur each distributed facilities and generates feasible production plans. Meta heuristic search algorithm is presented to solve the MIP problems. The experimental test evaluates the computational performance under a variety of problem scenarios.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.15-19
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• 1998

This paper concerns a bulk or semibulk cargo ship scheduling problem with a single loading port. This type of ship scheduling problem is frequently needed in real world for carrying minerals or agricultural produce from a major single production zone to many destinations scattered over a large area of the world. The first optimization model for this problem was introduced by Ronen (1986) as a nonlinear mixed integer program. The model developed in this paper is an improvement of his model in the sense that nonlinearities and numerous unnecessary integer variables have been eliminated. By this improvement we could expect real world instances of moderate sizes to be solved optimal solutions by commercial integer programming software. Similarity between the ship scheduling model and the capacitated facility location model is also discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.373-378
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• 2002

In fuzzy inferencing, most of conventional fuzzy controllers have problems of speed down in floating point operations of fuzzy membership functions in (0,1) as compared with integer operations. Therefore, in this paper, we propose a high-speed fuzzy controller with only integer operations. In this, for fast fuzzy computations, we use a scan line conversion algorithm to convert lines of each fuzzy linguistic term to the set of the closest integer pixels. We also implement a GUI (Graphic User Interface) application program for the convenient environments to modify and input fuzzy membership functions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.306-310
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• 2004

In this paper, we consider the Ring Loading Problem with integer demand splitting (RLP). The problem is given with a ring network, in which a required traffic requirement between each selected node pair must be routed on it. Each traffic requirement can be routed in both directions on the ring network while splitting each traffic requirement in two directions only by integer is allowed. The problem is to find an optimal routing of each traffic requirement which minimizes the capacity requirement. Here, the capacity requirement is defined as the maximum of traffic loads imposed on each link on the network. We formulate the problem as an integer program. By characterizing every extreme point solution to the LP relaxation of the formulation, we show that the optimal objective value of the LP relaxation is equal to p or p+0.5, where p is a nonnegative integer. We also show that the difference between the optimal objective value of RLP and that of the LP relaxation is at most 1. Therefore, we can verify that the optimal objective value of RLP is p+1 if that of the LP relaxation is p+0.5. On the other hand, we present a strengthened LP with size polynomially bounded by the input size, which provides enough information to determine if the optimal objective value of RLP is p or p+1.