• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.297-309
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• 1999

Resource Constrained Dynamic Multi-Projects Scheduling(RCDMPS) is intended to minimize the total processing time(makespan) of two or more projects sequentially arriving at the shop under restricted resources. The aim of this paper is to develop the new Tabu Search heuristic for RCDMPS to minimize makespan. We propose the insertion method to generate the neighborhood solutions in applying the Tabu Search for the RCDMPS and the diversification strategy to search the solution space diversely. The proposed diversification strategy apply the dynamic tabu list that the tabu list size is generated and renewed at each iteration by the complexity of the project, and change the proposed tabu attribute. In this paper, We use the dynamic tabu list for the diversification strategy and intensification strategy in the tabu search, and compare with other dispatching heuristic method to verify that the new heuristic method minimize the makespan of the problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.70-77
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• 2000

This paper proposes a method of solving a unit commitment problem using tabu search (TS) which is heuristic algorithm. Ts is a local search method that starts from any initial solution and attempts to determine a better solution using memory structures. In this paper, to reduce the computation time for finding the optimal solution, changing tabu list size as intensification strategy and path relinking method as diversification strategy are proposed. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with priority list, genetic algorithm(GA), and hybrid GA.

• Korean Management Science Review
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• v.22 no.1
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• pp.167-178
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• 2005

The 2DBPP(Two-Dimensional Bin Packing Problem) is a problem of packing each item into a bin so that no two items overlap and the number of required bins is minimized under the set of rectangular items which may not be rotated and an unlimited number of identical .rectangular bins. The 2DBPP is strongly NP-hard and finds many practical applications in industry. In this paper we discuss a tabu search approach which includes tabu list, intensifying and diversification Strategies. The HNFDH(Hybrid Next Fit Decreasing Height) algorithm is used as an internal algorithm. We find that use of the proper parameter and function such as maximum number of tabu list and space utilization function yields a good solution in a reduced time. We present a tabu search algorithm and its performance through extensive computational experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.311-314
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• 2004

The 2 DBPP(Two-Dimensional Bin Packing Problem) is a problem of packing each item into a bin so that no two items overlap and the number of required bins is minimized under the set of rectangular items which may not be rotated and an unlimited number of identical rectangular bins. The 2 DBPP is strongly NP-hard and finds many practical applications in industry. In this paper we discuss a tabu search approach which includes tabu list, intensifying and diversification strategies. The HNFDH(Hybrid Next Fit Decreasing Height) algorithm is used as an internal algorithm. We find that use of the proper parameter and function such as maximum number of tabu list and space utilization function yields a good solution in a reduced time. We present a tabu search algorithm and its performance through extensive computational experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.10-15
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• 2012

This paper considers an economic design problem of a tree-based network which is a kind of computer network. This problem can be modeling to be an objective function to minimize installation costs, on the constraints of spanning tree and maximum traffic capacity of sub tree. This problem is known to be NP-hard. To efficiently solve the problem, a tabu list coupled genetic algorithm approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.409-428
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• 1995

Job shop scheduling with m different machines and n different jobs is a NP-hard problem of combinatorial optimization. The purpose of the paper is to develop the heuristic method using tabu search for job shop scheduling to minimize makespan or mean flowtime. To apply tabu search to job shop scheduling problem, in this paper we propose the several move methods that employ insert moves in order to generate the neighbor solutions, and present the efficient rescheduling procedure that yields active schedule for a changed operation sequence by a move of operations. We also discuss the tabu search techniques of diversifying the search of solution space as well as the simple tabu search. By experiments, we find the appropriate tabu list size and tabu attributes, and analyze the proposed tabu search techniques with respect to the quality of solutions and the efforts of computation. The experimental results show that the proposed tabu search techniques using long-term memory function have the ability to search a good solution, and are more efficient in the mean flowtime minimization problem than in the makespan minimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.798-806
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• 2003

Structural optimization has been carried out in continuous or discrete design space. Methods for continuous design have been well developed though they are finding the local optima. On the contrary, the existing methods for discrete design are extremely expensive in computational cost or not robust. In this research, an algorithm using tabu search is developed fur the discrete structural designs. The tabu list and the neighbor function of the Tabu concepts are introduced to the algorithm. It defines the number of steps, the maximum number for random searches and the stop criteria. A tabu search is known as the heuristic approach while genetic algorithm and simulated annealing algorithm are attributed to the stochastic approach. It is shown that an algorithm using the tabu search with random moves has an advantage of discrete design. Furthermore, the suggested method finds the reliable optimum for the discrete design problems. The existing tabu search methods are reviewed. Subsequently, the suggested method is explained. The mathematical problems and structural design problems are investigated to show the validity of the proposed method. The results of the structural designs are compared with those from a genetic algorithm and an orthogonal array design.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.528-536
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• 2001

This paper proposes a method of solving a unit commitment problem using parallel tabu search(PTS) approach. Tabu search is a heuristic optimization method that has the tabu list to control the search process. To improve the searching ability of a global solution, we used a method of exchanging solutions among connected processors as a diversification strategy, and to reduce the computation time, a new evaluating method was proposed which evaluates only a changed par. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with other conventional methods.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.

• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.575-588
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• 2007

In this paper, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search. The first algorithm utilizes the features of short-term memory (tabu list) facility and aspiration criteria and the other has long-term memory (back-tracking) facility in addition to the aforementioned features. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Allowable stress design (ASD) specification, maximum drift (lateral displacement) and interstorey drift constraints were imposed on the frames. The algorithms were applied to the optimum design of three space frame structures. The designs obtained using the two algorithms were compared to each other. The comparisons showed that the second algorithm resulted in lighter frames.