• Korean Management Science Review
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• v.18 no.1
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• pp.155-164
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• 2001

The widespread diffusion of Internet has enables every college and education institute to develope cyber education systems to meet the multiple needs of students, but it is not true that the effectiveness of cyber education is fruitful in terms of evaluation systems. Most of the early developed web-based evaluation systems for cyber education require that all the students should solve uniformed test set which are included in the predetermined static HTML pages. Therefore, it is impossible to dynamically provide a test set with consistency and reliability. This paper purpose to describe the employment of simulated annealing in cyber testbank system for test set generation that satisfy all constraints. The constraints include number of items for each skill, method, domain, topic, and so on. This research developed two phase heuristic combining sequential test set generation algorithm with simulated annealing. As a result of computer simulations, it was found that the two phase heuristic outperforms the other algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.715-722
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• 2005

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used products while satisfying the demand of their parts or components over a planning horizon. The case of single product type with assembly structure is considered for the objective of minimizing the sum of disassembly operation and inventory holding costs. In particular, the resource capacity constraint is explicitly considered. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To show the performance of the heuristic, computational experiments are done on a number of randomly generated problems, and the test results show that the algorithm can give near optimal solutions within a very short amount of computation time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.59-71
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• 2005

In this paper we address a design problem for hub and spoke transportation networks and then consider a capacitated hub locations problem with direct shipment (CHLPwD). We determine the location of hubs, the allocation of nodes to hubs, and direct shipment paths in the network, with the objective of minimizing the total cost in the network. An evolutionary algorithm is developed here to solve the CHLPwD. To do this, we propose the representation and the genetic operators suitable for the problem and adopt a heuristic method for the allocation of nodes to hubs. To enhance the search capability, problem-specific information is used in our evolutionary algorithm. The proposed algorithm is compared with the heuristic method in terms of solution quality and computation time. The experimental results show that our algorithm can provide better solutions than the heuristic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1220-1228
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• 1999

In this paper, we deal with an important network design problem in providing multimedia telecommunication services. The problem is to find an optimal gateway location and fiber routing, while minimizing the total cost. The cost elements are the installation cost of add-drop multiplexer and fiber cables. We have developed effective heuristic procedures for the problem. The performance of the developed heuristic shows promising computational results.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.123-134
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• 2003

Fire Sequencing Problem (FSP) is to find a sequence of targets, where there exist a number of targets with different time units required to fire. Because of the weapon's specifications and the size of the targets, several weapons may fire on the same targets, and the time units required on firing for each weapon may be different from each other. The objective is to minimize the completion time of firing for given number of targets. Mathematical formulation is given, and the heuristic algorithm based on the paring of targets in advance is suggested. Performance of the heuristic is evaluated by comparison of heuristic appeared in the literature through the computational experiments.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.47-55
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• 1999

This paper develops an efficient heuristic algorithm for scheduling workforce level that can accommodate all the requested maintenance jobs. Each job has its own release and due dates as well as man-day requirement, and must be scheduled in a non-interrupted time interval, namely, without preemption. Duration of each job is not fixed, but to be determined within given specific range. The objective is to minimize workforce level to complete all the requested maintenance jobs. We show that the problem can be seen as a variant of the two-dimensional bin-packing problem with some additional constraints. A non-linear mixed integer programming model for the problem is developed, and an efficient heuristic algorithm based on bin-packing algorithms is proposed. In order to evaluate goodness of the solution obtained from the proposed algorithm, a scheme for getting a good lower bound for the optimum solution is presented and analyzed. The computational experiment shows that the proposed algorithm performs quite satisfactorily.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.451-467
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• 1997

Tabu search (TS) is a useful strategy that has been successfully applied to a number of complex combinatorial optimization problems. By guiding the search using flexible memory processes and accepting disimproved solutions at some iterations, TS helps alleviate the risk of being trapped at a local optimum. In this article, we propose TS-based heuristics for solving a class of clustering problems, and compare the relative performances of the TS-based heuristic and the simulated annealing (SA) algorithm. Computational experiments show that the TS-based heuristic with a long-term memory offers a higher possibility of finding a better solution, while the TS-based heuristic without a long-term memory performs better than the others in terms of the combined measure of solution quality and computing effort required.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.205-215
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• 2008

convergence networks (BcN). The problem seeks to minimize the total cost of switch and cable while satisfying the requirement of demand and quality of service (QoS). We develop mixed integer programming models to obtain the optimal switch location of the access network. We develop a Tabu Search (TS) heuristic algorithm for finding a good feasible solution within a reasonable time limit. We propose real networks with up to 25 nodes and 180 demands. In order to demonstrate the effectiveness of the proposed algorithm, we generate lower bounds from nonlinear QoS relaxation problem. Computational results show that the proposed heuristic algorithm provides upper bounds within 5% optimality gap in 10 seconds.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.73-82
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• 2011

There are a lot of people trying to solve the Traveling Salesman Problem (TSP) by using the Meta Heuristic Algorithms. TSP is an NP-Hard problem, and is used in testing search algorithms and optimization algorithms. Also TSP is one of the models of social problems. Many methods are proposed like Hybrid methods and Custom-built methods in Meta Heuristic. In this paper, we propose the S-MINE Algorithm to use the MINE Algorithm introduced in 2009 on the TSP.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.237-242
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• 2009

The classical vehicle routing problem (VRP) can be extended by including customers who want to send goods to the depot. This type of VRP is called the vehicle routing problem with pickups and deliveries (VRPPD). This study proposes a novel way to solve VRPPD by introducing a two-phase heuristic routing algorithm which consists of a clustering phase and uses the geometrical center of a cluster and route establishment phase by applying a two-way search of each route after applying the TSP algorithm on each route. Experimental results show that the suggested algorithm can generate better initial solutions for more computer-intensive meta-heuristics than other existing methods such as the giant-tour-based partitioning method or the insertion-based method.