• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.392-392
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• 2000

This study performs optimization of paper mill scheduling using MINLP(Mixed-Integer Non-Linear Programming) method and 2-step decomposing strategy. Paper mill process is normally composed of five units: paper machine, coater, rewinder, sheet cutter and roll wrapper/ream wrapper. Various kinds of papers are produced through these units. The bottleneck of this process is how to cut product papers efficiently from raw paper reel and this is called trim loss problem or cutting stock problem. As the trim must be burned or recycled through energy consumption, minimizing quantity of the trim is important. To minimize it, the trim loss problem is mathematically formulated in MINLP form of minimizing cutting patterns and trim as well as satisfying customer's elder. The MINLP form of the problem includes bilinearity causing non-linearity and non-convexity. Bilinearity is eliminated by parameterization of one variable and the MINLP form is decomposed to MILP(Mixed-Integer Linear programming) form. And the MILP problem is optimized by means of the optimization package. Thus trim loss problem is efficiently minimized by this 2-step optimization method.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.13-21
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• 2014

The set covering problem (SCP) is one of representative combinatorial optimization problems, which is defined as the problem of covering the m-rows by a subset of the n-columns at minimal cost. This paper proposes a method utilizing Integer Programming-based Local Search (IPbLS) to solve the set covering problem. IPbLS is a kind of local search technique in which the current solution is improved by searching neighborhood solutions. Integer programming is used to generate neighborhood solution in IPbLS. The effectiveness of the proposed algorithm has been tested on OR-Library test instances. The experimental results showed that IPbLS could search for the best known solutions in all the test instances. Especially, I confirmed that IPbLS could search for better solutions than the best known solutions in four test instances.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.92-99
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• 2004

We consider the ATM switching node location problem (ANLP). In this problem, there are two kinds of facilities, hub facilities and remote facilities, with different capacities and installation costs. We are given a set of customers with each demand requirements, a set of candidate installation sites of facilities, and connection costs between facilities. We need to determine the locations to place facilities, the number of facilities for each selected location, the set of customers who are connected to each installed hub via installed remote facilities with minimum cost, while satisfying demand requirements of each customer. We formulate this problem as a general integer programming problem and solve it to optimality. In this paper, we present a preprocessing procedure to tighten the formulation and develop a branch-and-price algorithm. In the algorithm, we consider the integer knapsack problem as the column generation problem. Computational experiments show that the algorithm gives optimal solutions in a reasonable time.

• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.46-54
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• 2006

We propose an optimization method for PCB assembly lines including multiple surface mounters. To increase the productivity of PCB assembly line, the component allocation, feeder assignment, and assembly sequence of each surface mounter should be optimized. The optimization Problem is formulated as an integer programming problem. We divide the overall problem into two hierarchical sub-problems: forward-path problem and backward-path problem. The clustering algorithm and branch-and-bound algorithm are applied to solve the forward-path problem. The assignment algorithm and connection algorithm are applied to solve the backward-path problem. Simulation results are presented to verify the usefulness of the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.2
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• pp.45-50
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• 1984

This paper is concerned with the facility location-allocation problem (FLAP) with multiple objectives. A branch-and-bound procedure is presented to solve the mixed zero-one integer goal programming problem which is to determine facility locations from given candidate locations and to allocate facility capacity to given customer markets simultaneously. A numercial example is given to illustrate this procedure.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.293-303
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• 2006

This paper describes a numerical scheme for optimal control of a time-dependent linear system to a moving final state. Discretization of the corresponding differential equations gives rise to a linear algebraic system. Defining some binary variables, we approximate the original problem by a mixed integer linear programming (MILP) problem. Numerical examples show that the resulting method is highly efficient.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.7-13
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• 2004

In this paper, machine cell formation problem is discussed. To reflect precisely actual manufacturing situations such as routing sequences, production quantities, and machining (or operation) characteristics, a new network presentation (or the problem is proposed. It is formulated as a simple 0-1 quadratic programming model with linear constraints. Then, the model is converted into a 0-1 integer programming model using a variable transformation technique. Lastly, some computational results are presented.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.141-153
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• 2017

A binary integer programming model is proposed for a complex timetabling problem in a university faculty which conducts various degree programs. The decision variables are defined with fewer dimensions to economize the model size of large scale problems and to improve modeling efficiency. Binary matrices are used to incorporate the relationships between the courses and students, and the courses and teachers. The model includes generally applicable constraints such as completeness, uniqueness, and consecutiveness; and case specific constraints. The model was coded and solved using Open Solver which is an open-source optimizer available as an Excel add-in. The results indicate that complicated timetabling problems with large numbers of courses and student groups can be formulated more efficiently with fewer numbers of variables and constraints using the proposed modeling framework. The model could effectively generate timetables with a significantly lower number of work hours per week compared to currently used timetables. The model results indicate that the particular timetabling problem is bounded by the student overlaps, and both human and physical resource constraints are insignificant.

• Korean Management Science Review
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• v.24 no.1
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• pp.35-43
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• 2007

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 qualify. 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.

• 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.