• IE interfaces
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• v.22 no.2
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• pp.116-125
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• 2009

We revisit the assembly block storage location assignment problem (ABSLAP) at a shipyard, in order to compensate for the deficiency in performance verification of the heuristic ABSLAP algorithm developed by the previous study. In this paper, we formulate a mathematical programming model of the ABSLAP, refine elaborately the heuristic ABSLAP algorithm, and show the performance of the developed mathematical programming model and the revised heuristic ABSLAP algorithm. In addition, we explain simulation experiments conducted using the revised heuristic ABSLAP algorithm to investigate the influences of block stockyard layouts and production schedule instability on the block stockyard operations.

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.127-142
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• 2006

In this paper, we present a frequency reassignment problem (FRP) that arises when we add new base stations to resolve hot-spots or to expand the coverage of a code division multiple access (CDMA) network. For this problem, we develop an integer programming (IP) model along with some valid inequalities and preprocessing rules. Also, we develop an effective heuristic procedure that solves two sub-problems induced from the original problem in repetition. Computational results show that the proposed heuristic procedure finds a feasible solution of good quality within reasonable computation time. Also, the lower bound by-produced from the heuristic procedure is quite strong.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.656-661
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• 2013

In Guided Scrambling (GS) encoding for the holographic storage, after scrambling augmented source word into codeword, the best codeword satisfying modulation constraint is determined. Modulation constraints considered in this paper are strength which is the minimum number of transition between '0' and '1' in each row and column of codeword array and the symbol balancedness of codeword array. In this paper, we show that GS encoding procedure can be formulated as an integer programming model and develop a fast neighborhood search heuristic for fast computation of control bits. In the simulation, we compared the performance of heuristic algorithm with the integer programming model for various array and control bit size combinations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.127-133
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• 2006

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 quality. 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. Also, we developed a web based scheduling and monitoring system for a zinc alloy production process using the developed heuristic algorithm. By using this system, we could find a monthly zinc alloy production schedule that significantly reduces the total number of setup changes.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.21-29
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• 2015

The set partitioning problem is a well-known NP-hard combinatorial optimization problem, and it is formulated as an integer programming model. This paper proposes an Integer Programming-based Local Search for solving the set partitioning problem. The key point is to solve the set partitioning problem as the set covering problem. First, an initial solution is generated by a simple heuristic for the set covering problem, and then the solution is set as the current solution. Next, the following process is repeated. The original set covering problem is reduced based on the current solution, and the reduced problem is solved by Integer Programming which includes a specific element in the objective function to derive the solution for the set partitioning problem. Experimental results on a set of OR-Library instances show that the proposed algorithm outperforms pure integer programming as well as the existing heuristic algorithms both in solution quality and time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1056-1064
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• 2003

The Euclidean steiner tree problem (ESTP) is to find a minimum-length euclidean interconnection of a set of points in the plane. It is well known that the solution to this problem will be the minimal spanning tree (MST) on some set steiner points, and the ESTP is NP-complete. The ESTP has received a lot of attention in the literature, and heuristic and optimal algorithms have been proposed. In real field, heuristic algorithms for ESTP are popular. A key performance measure of the algorithm for the ESTP is the reduction rate that is achieved by the difference between the objective value of the ESTP and that of the MST without steiner points. In recent survey for ESTP, the best heuristic algorithm showed around $3.14\%$ reduction in the performance measure. We present a evolution programming (EP) for ESTP based upon the Prim algorithm for the MST problem. The computational results show that the EP can generate better results than already known heuristic algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.18
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• pp.7-15
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• 1988

This study is concerned with selecting mutually dependent quality improvement alternatives with resource constraints. These qualify improvement alternatives art different fro the tradition at alternatives which are independent from each other. In other words, selection of any improvement alternative requires other related specific improvement. Also the overall product quality in a multi stage manufacturing process is characterized by a complex multiplication method rather than a simple addition method which dose not allow to solve a linear knapsack problem despite its popularity in the traditional study. This study suggests a non-linear integer programming model for selecting mutually dependent quality improvement alternatives in multi-stage manufacturing process. In order to apply the model to selecting alternatives. This study also suggests a heuristic mode1 based on a dynamic programming model which is more practical than the non-linear integer programming model. The logic of the heuristic model enables 1) to estimate improvement effectiveness values on all improvement alternatives specifically defined for this study. 2) to arrange the effectiveness values in a descending order, and 3) to select the best one among the alternatives based on their forward and backward linkage relationships. This process repeats to selects other best alternatives within the resource constraints. This process is presented in a Computer programming in Appendix A. Alsc a numerical example of model application is presented in Chapter 4.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.1-11
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• 2001

This paper considers the scheduling of cell-based handoffs to balance the traffic in a fiber-optic microcelluar system. In the system depending on the order of cell based handoff, periodical balancing of the traffic among microcells can be achieved. The cell based handoff problem is formulated as a dynamic programming and the computational complexity is analyzed. Since the scheduling problem requires real time solution, heuristic algorithms are proposed and the computational results are discussed.