• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.31-41
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• 1995

The maximum Origin-Destination Flow Path Problem (MODFP) in an Acyclic Network has known as NP-hard. K. S. Sung has suggested on Optimal Algorithm for MODFP based on the Pseudo flo or arc and the K-th shortest path algorithm. When we try to solve MODFP problem by general Branch and Bound Method (BBM), the upper and lower bounds of subproblems are so weak that the BBM become very inefficient. Here we utilized the Pseudo flow of arc' for the tight bounds of subproblems so that it can produce an efficient BBM for MODFP problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.501-505
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• 1998

In this paper, an LP problem with convex polyhedral objective coefficients is treated. In the problem, the interactivities of the uncertain objective coefficients are represented by a bounded convex polyhedron (a convex polytope). We develop a computation algorithm of a maxmin achievement rate solution. To solve the problem, first, we introduce the relaxation procedure. In the algorithm, a sub-problem, a bilevel programing problem, should be solved. To solve the sub-problem, we develop a solution method based on a branch and bound method. As a result, it is shown that the problem can be solved by the repetitional use of the simplex method.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.73-80
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• 1986

This paper deals with the problem of the optimal location of warehouses in the two stage distribution system, i.e., the distribution system where the product is transported from plants to customer areas via warehouses. The Problem is formulated with a zero-one mixed integer programming and an efficient branch and bound algorithm is then used to solve the problem. In order to obtain the solution of this problem, this paper shows the procedure of conversion of two stage distribution system into one stage distribution system. An improved method of solving the linear programming at the nodes and branching decision rule is also showed by this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.78-101
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• 2017

High-quality industrial control is critical to ensuring production quality, reducing production costs, improving management levels and stabilizing equipment and long-term operations. WiFi-based Long Distance (WiLD) networks have been used as remote industrial control networks. Real-time performance is essential to industrial control. However, the original mechanism of WiLD networks does not minimize end-to-end delay and restricts improvement of real-time performance. In this paper, we propose two algorithms to obtain the transmitting/receiving phase cycle length for each node such that real time constraints can be satisfied and phase switching overhead can be minimized. The first algorithm is based on the branch and bound method, which identifies an optimal solution. The second is a fast heuristic algorithm. The experimental results show that the execution time of the algorithm based on branch and bound is less than that of the heuristic algorithm when the network is complex and that the performance of the heuristic algorithm is close to the optimal solution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.1-13
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• 1998

The purpose of this paper is to formulate the three-dimensional loading problem and to develop an exact algorithm. The three-dimensional loading problem is not only to load as many boxes as possible, but also to ensure load stability. In this Paper, we propose formulation by zero-one integer programming. Further we propose as an algorithm the branch-and-bound enforced by efficient bounding criteria. As an upper bound, we use the solution of the Lagrangean relaxation problem which relaxes constraints of zero-one IP, and as a lower bound, we use a heuristic solution induced by the solution of the Lagrangean relaxation problem. Last, we show computational experiments on convergency of upper and lower bounds.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.213-219
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• 2016

This paper presents a branch-and-bound algorithm for solving the concave minimization problem with upper bounded variables whose single constraint is linear. The algorithm uses simplex as partition element. Because the convex envelope which most tightly underestimates the concave function on the simplex is uniquely determined by solving the related linear equations. Every branching process generates two subsimplices one lower dimensional than the candidate simplex by adding 0 and upper bound constraints. Subsequently the feasible points are partitioned into two sets. During the bounding process, the linear programming problems defined over subsimplices are minimized to calculate the lower bound and to update the incumbent. Consequently the simplices which do certainly not contain the global minimum are excluded from consideration. The major advantage of the algorithm is that the subproblems are defined on the one less dimensinal space. It means that the amount of work required for the subproblem decreases whenever the branching occurs. Our approach can be applied to solving the concave minimization problems under knapsack type constraints.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.272-281
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• 1988

The problem of optimal transmission system planning is to find the most economical locations and time of transmission line construction under the various constraints such as available rights-of-way, finances, the technical characteristics of power system, and the reliability criterion of power supply, and so on. In this paper the constraint of right-of-way is represented as a finite set of available rights-of-way. And the constructed for a unit period. The electrical constraints are represented in terms of line overload and steady state stability margin. And the reliability criterion is dealt with the suppression of failure cost and with single-contingency analysis. In general, the transmission planning problem requires integer solutions and its objective function is nonlinear. In this paper the objective function is defined as a sum of the present values of construction cost and the minimum operating cost of power system. The latter is represented as a sum of generation cost and failure cost considering the change of yearly load, economic dispatch, and the line contingency. For the calculation of operating cost linear programming is adopted on the base of DC load flow calculation, and for the optimization of main objective function nonlinear Branch-and-Bound algorithm is used. Finally, for improving the efficiency of B & B algorithm a new sensitivity analysis algorithm is proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.3
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• pp.58-66
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• 2003

The cut tree approach of Montreuil and Ratliff [16] and eigenvector approach [10] are used to automatically draw a feasible facility layout with aisle structure. The department arrangement can minimize an aisle distance criterion considering door locations and dimension constraints. The aisle distance is measured by the door to door distance between departments. An eigenvector and cut tree approaches [1] are implemented based on the branch and bound technique in Kim et al. [2] in order to obtain feasible layouts. Then, the algorithm to fix the door location of each department is developed. After the door locations are determined, the factory layout is evaluated in terms of aisle distance. The aisle structure is obtained by expanding the original layout. The solution is kept until we will find better factory layout. The proposed approach based on the branch and bound technique, in theory, will provide the optimal solution. If the runs are time and/or node limited, the proposed method is a strong heuristic. The technique is made further practical by the fact that the solution is constrained such that the rectangular shape dimensions length(l) and width(w) are fixed and a perfect fit is generated if a fit is possible.

• 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.