• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.46-49
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• 2003

This paper proposes a method to solve expansion problem for a transmission network, given future generation and load strategy, and alternative types of lines available, subject to load, reliability and right of way constraints, the problem is formulated as a series of zero one integer programs which are solved by an efficient branch and bound algorithm A study test result on the 63-buses test system shows that the proposed method is practical and efficiently applicable to the transmission expansion planning.

• Journal of Navigation and Port Research
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• v.28 no.2
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• pp.129-133
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• 2004

Column subtraction, originally proposed by Harche and Thompson(1994), is an exact method for solving large set covering, packing and partitioning problems. Since the constraint set of ship scheduling problem(SSP) have a special structure, most instances of SSP can be solved by LP relaxation This paper aim, at applying the column subtraction method to solve SSP which am not be solved by LP relaxation For remained instances of unsolvable ones, we subtract columns from the finale simplex table to get another integer solution in an iterative manner. Computational results having up to 10,000 0-1 variables show better performance of the column subtraction method solving the remained instances of SSP than complex branch and-bound algorithm by LINDO.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.567-578
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• 1996

In relational databases the number of disk accesses depends on the amount of data transferred from disk to main memory for processing the transactions. N-ary vertical partitioning of the relation can often result in a decrease in the number of disk accesses, since not all attributes in a tuple are required by each transactions. In this paper, a 0-1 integer programming model for solving n-ary vertical partitioning problem minimizing the number of disk accesses is formulated and a branch-and-bound method is used to solve it. A preprocessing procedure reducing the number of variables is presented. The algorithm is illustrated with numerical examples and is shown to be computationally efficient. Numerical experiments reveal that the proposed method is more effective in reducing access costs than the existing algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.35-42
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• 1990

This paper deals with a single machine scheduling problem with a quadratic penalty function of completion times. The objective is to find a optimal sequence which minimizes the total penalty. A new type of node elimination procedure and precedence relation is developed that determines the ordering between adjacent jobs and is incorporated into a branch and bound algorithm. In addition, modified penalty function is considered and numerical examples are provided to test the effectiveness of the optimum algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.1-8
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• 1985

By introducing the concept of reliability of parallel systems the set covering. A branch-and-bound algorithm is developed and illustrated by a numerical example. The procedure has been coded and its computational efficiency is studied.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.519-527
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• 1995

By finding some new properties, we develop an O($r_{max}n^2$) algorithm for the generalized multiple choice linear knapsack problem where $r_{max}$ is the largest multiple choice number and n is the total number of variables. The proposed algorithm can easily be embedded in a branch-and-bound procedure due to its convenient structure for the post-optimization in changes of the right-hand-side and multiple choice numbers. A numerical example is presented.

• Nonlinear Functional Analysis and Applications
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• v.26 no.3
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• pp.611-628
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• 2021

In this paper, we propose a new branch-reduction-and-bound algorithm to solve the nonlinear knapsack problems by using general discrete monotonic optimization techniques. The specific properties of the problem are exploited to increase the efficiency of the algorithm. Computational experiments of the algorithm on problems with up to 30 variables and 5 different constraints are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.65-69
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• 1990

Two different algorithms for traveling salesman problem(TSP) will be discussed. One is the engineering approach to the TSP. The other one is Branch-and-Bound algorithm to take advantage of the special structure of combinational problems. Also a generalization of TSP will be presented.

• Korean Management Science Review
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• v.19 no.1
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• pp.55-66
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• 2002

Given a directed network, a designated arc, and lowers and upper bounds for the distance of each arc, the preprocessing shortest path problem Is a decision problem that decides whether there is some choice of distance vector such that the distance of each arc honors the given lower and upper bound restriction, and such that the designated arc is on some shortest path from a source node to a destination notre with respect to the chosen distance vector. The preprocessing shortest path problem has many real world applications such as communication and transportation network management and the problem is known to be NP-complete. In this paper, we develop an algorithm that solves the problem using the structural properties of shortest paths.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.53-66
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• 1989

The Public Vehicle Routing Problem (PVRP) is to find the minimum total cost routes of M or less Public-Vehicles to traverse the required arcs(streets) at least once, and return to their starting depot on a directed network. In this paper, first, a mathematical model is formulated as minimal cost flow model with illegal subtour elimination constraints, and with the fixed cost and routing cost as an objective function. Second, an efficient branch and bound algorithm is developed to obtain an exact solution. A subproblem in this method is a minimal cost flow problem relaxing illegal subtour elimination constraints. The branching strategy is a variable dichotomy method according to the entering nonrequired arcs which are candidates to eneter into an illegal subtour. To accelerate the fathoming process, a tighter lower bound of a candidate subproblem is calculated by using a minimum reduced coast of the entering nonrequired arcs. Computational results based on randomly generated networks report that the developed algorithm is efficient.