• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.1
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• pp.99-115
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• 1990

This paper is concerned with the unit commitment problem in an electric power system with both thermal and pumped-storage hydroelectric units. This is a mixed integer programming problem and the Lagrangean relaxation method is used. We show that the relaxed problem decomposes into two kinds of subproblems : a shortest-path problem for each thermal unit and a minimum cost flow problem for each pumped-storage hydroelectric unit. A method of obtaining an incumbenet solution from the solution of a relaxed problem is presented. The Lagrangean multipliers are updated using both subgradient and incremental cost. The algorithm is applied to a real Korean power generation system and its computational results are reported and compaired with other works.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.2
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• pp.33-44
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• 1990

An efficient algorithm is developed for the linear programming relaxation of generalized multiple choice knaspack problem. The generalized multiple choice knaspack problem is an extension of the multiple choice knaspack problem whose relaxed LP problem has been studied extensively. In the worst case, the computational coimplexity of the proposed algorithm is of order 0(n. $n_{max}$)$^{2}$), where n is the total number of variables and $n_{max}$ denotes the cardinality of the largest multiple choice set. The algorithm can be easily embedded in a branch-and-bound procedure for the generalized multiple choice knapsack problem. A numerical example is presented and computational aspects are discussed.sed.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.137-158
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• 1992

We study the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are pnelized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. We develop Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP. In addition, several heuristic algorithms are presented and performances are tested using computational experiments. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We also present a method to phase into a target cyclic schedule for infinite horizon problems. These can be used as a practical scheduling tool for temporarily overloaded facilities or to reschedule production after a disruption.

• Journal of the military operations research society of Korea
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• v.10 no.1
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• pp.41-55
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• 1984

Clarke-Wright algorithm is a well-known heuristic algorithm for the vehicle routing problem, that is, the problem to find routes through which vehicles deliver goods to retailers. The purpose of this paper is to extend the Clarke-Wright algorithm to the vehicle routing problem with the following restrictions: ${\cdot}$ capacities of vehicles may not be the same ${\cdot}$ vehicles should pick up empty boxes on the way back ${\cdot}$ there is a deadline before delivery should be completed for every retailer ${\cdot}$ only certain kinds of vehicles may enter the unloading sites of retailers. This paper modifies the Clarke-Wright algorithm for this problem and shows how to solve a real problem by the newly developed algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.49-62
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• 1998

In the ring loading problem, traffic demands are given for each pair of nodes in an undirected ring network with n nodes and a flow is routed in either of the two directions, clockwise and counter-clockwise. The load of a link is the sum of the flows routed through the link and the objective of the Problem is to minimize the maximum load on the ring. In the ring loading problem with integer demand splitting, each demand can be split between the two directions and the flow routed in each direction is restricted to integers. Recently, Vachani et al. ［INFORMS J. Computing 8 (1996) 235-242］ have developed an Ο(n$^3$) algorithm for solving this integer version of the ring loading problem and independently, Schrijver et al. ［to appear in SIAM J. Disc. Math.］ have presented an algorithm which solves the problem with ｛0,1｝ demands in Ο（n$^2$｜K｜ ) time where K denotes the index set of the origin-desㅇtination pairs of nodes having flow demands. In this paper, we develop an algorithm which solves the problem in Ο(n ｜K｜) time.

• Research in Mathematical Education
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• v.9 no.1 s.21
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• pp.1-9
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• 2005

This paper investigates instructional strategies with potential for improving students' achievement in word problem solving. This review compares and analyzes the direct instruction (DI) and cognitively guided instruction (CGI) research on K-3 word problem solving mathematics students in a demonstration of my position that teachers need to understand student mathematical thinking to enhance students' achievement in word problem solving. CGI provides a more appropriate instructional model than DI for teaching word problem solving. For example, student-centered, conceptual understanding, and children's informal or invented problem solving strategies communicating with each other mathematically, etc. Korean teachers and teacher educators need to consider implementing CGI teaching strategies.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.106-116
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• 1999

The purpose of this study is to present a method for determining the k most vital arcs in the maximum flow problem using genetic algorithms. Generally, the problem which determine the k most vital arcs in maximum flow problem has known as NP-hard. Therefore, in this study we propose a method for determining all the k most vital arcs in maximum flow problem using genetic algorithms. First, we propose a genetic algorithm to find the k most vital arcs removed at the same time and then present the expression and determination method of individuals compatible with the characteristics of the problem, and specify the genetic parameter values of constitution, population size, crossover rate, mutation rate and etc. of the initial population which makes detecting efficiency better. Finally, using the proposed algorithms, we analyzed the performance of searching optimal solution through computer experiment. The proposed algorithms found all alternatives within shorter time than other heuristic methods. The method presented in this study can determine all the alternatives when there exists other alternative solutions.

• Journal of Educational Research in Mathematics
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• v.12 no.2
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• pp.265-274
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• 2002

The purpose of the paper is to provide the importance of matacognition as a factor to correct the errors generated by the intuition. For this, first of all, we examine not only the role of metacognition in mathematics education but also the errors generated by the intuition in the mathematical problem solving process. Next, we research the possibility of using metacognition as a factor to correct the errors in the mathematical problem solving process via both the related theories about the metacognition and an example. In particular, we are able to acknowledge the importance of the role of metacognition throughout the example in the process of the problem solving It is not difficult to conclude from the study that emphasis on problem solving will enhance the development of problem solving ability via not only the activity of metacognition but also intuitive thinking. For this, it is essential to provide an environment that the students can experience intuitive thinking and metacognitive activity in mathematics education .

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.93-113
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• 2007

In the previous research, we considered a logistics brokerage problem with the objective of minimizing total transportation lead time of freights in a logistics e-marketplace, in which a logistics brokerage agent intermediates empty vehicles and freights registered by car owners and shippers [7]. However, in the logistics e-marketplace, transportation due date tardiness is more important than the transportation lead time, since transportation service level is critically determined by whether the due date is met or not. Therefore, in this paper, we deal with the logistics brokerage problem with the objective of minimizing total tardiness of freights. Hungarian method based matching algorithms, real time matching(RTM), periodic matching(PM), and fixed matching(FM), are used for solving the problem considered in this paper. In order to test performance of the proposed algorithms, we perform computational experiments on a various problem instances. The results show that the waiting-and-matching algorithms, PM and FM, also give better performance than real time matching strategy, RTM, for the total tardiness minimization problem as the algorithms did for the total lead time minimization problem.

• Research in Mathematical Education
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• v.12 no.3
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• pp.179-191
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• 2008

Although problem solving was a major focus of mathematics education research in many countries throughout the 1990s, not enough is known about how people best acquire problem-solving skills. This paper is an attempt to advance further development of problem-solving skills of talented school students through combination of some methods accessible from curriculum knowledge and more special techniques that are beyond curriculum. Analysis of various problems is provided in detail. Educational aspects of challenging problems in mathematical contests up to IMO level are, also, taken into account and discussed in the paper.