• Title/Summary/Keyword: Tabu Search Method

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A Tabu Search Approach for Resource Constrained Dynamic Multi-Projects Scheduling (자원제약하의 동적 다중 프로젝트 일정계획에 Tabu Search 적용)

  • 윤종준;이화기
    • 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.

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Tabu Search for Job Shop Scheduling (Job Shop 일정계획을 위한 Tabu Search)

  • Kim, Yeo-Keun;Bae, Sang-Yun;Lee, Deog-Seong
    • 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.

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Design of PID Controller using an Improved Tabu Search (개선된 타부 탐색을 이용한 PID 제어기 설계)

  • 이양우;박경훈;김동욱
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.5
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    • pp.323-330
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    • 2004
  • In this paper, we propose a design method of PID controller using an improved Tabu Search. Tabu Search is improved by neighbor solution creation using Gaussian random distribution and generalized Hermite Biehler Theorem for stable bounds. The range of admissible proportional gains are determined first in closed form. Next the optimal PID gains are selected by improved Tabu Search. The results of Computer simulations represent that the proposed Tabu Search algorithm shows a fast convergence speed and a good control performance.

Ooptimum Design Damping Plate by Combined Method of Genetic Algorithm and Random Tabu Search Method (유전알고리즘과 Tabu탐색법에 의한 제진판의 최적설계)

  • 양보석;전상범;유영훈;최병근
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1997.10a
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    • pp.184-189
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    • 1997
  • This paper introduces a new combined method by genetic algorithm and random tabu search method as optimization algorithm. Genetic algorithm can search the global optimum and tabu search method is very fast in speed. The optimizing ability of new combined method is identified by comparing other optimizing algorithm and used for optimum design of damping plate.

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Low complexity hybrid layered tabu-likelihood ascent search for large MIMO detection with perfect and estimated channel state information

  • Sourav Chakraborty;Nirmalendu Bikas Sinha;Monojit Mitra
    • ETRI Journal
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    • v.45 no.3
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    • pp.418-432
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    • 2023
  • In this work, we proposed a low-complexity hybrid layered tabu-likelihood ascent search (LTLAS) algorithm for large multiple-input multiple-output (MIMO) system. The conventional layered tabu search (LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low-complexity likelihood ascent search (LAS) operations. The block-based detection approach is considered to maintain a higher signal-to-noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10-3.

Tabu Search methods to minimize the number of tardy jobs in nonidentical parallel machine scheduling problem (동일하지 않는 병렬기계 시스템에서 지연작업수를 최소화하는 Tabu Search 방법)

  • 전태웅;강맹규
    • Korean Management Science Review
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    • v.12 no.3
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    • pp.177-185
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    • 1995
  • This paper presents a Tabu Search method to minimize a number of tardy jobs in the nonidentical parallel machine scheduling. The Tabu Search method employs a restricted neighborhood for the reduction of computation time. In this paper, we use two different types of method for a single machine scheduling. One is Moore's algorithm and the other is insertion method. We discuss computational experiments on more than 1000 test problems.

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Optimum Allocation of Pipe Support Using Combined Optimization Algorithm by Genetic Algorithm and Random Tabu Search Method (유전알고리즘과 Random Tabu 탐색법을 조합한 최적화 알고리즘에 의한 배관지지대의 최적배치)

  • 양보석;최병근;전상범;김동조
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.71-79
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    • 1998
  • This paper introduces a new optimization algorithm which is combined with genetic algorithm and random tabu search method. Genetic algorithm is a random search algorithm which can find the global optimum without converging local optimum. And tabu search method is a very fast search method in convergent speed. The optimizing ability and convergent characteristics of a new combined optimization algorithm is identified by using a test function which have many local optimums and an optimum allocation of pipe support. The caculation results are compared with the existing genetic algorithm.

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A Cooperative Parallel Tabu Search and Its Experimental Evaluation

  • Matsumura, Takashi;Nakamura, Morikazu;Tamaki, Shiro;Onaga, Kenji
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.245-248
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    • 2000
  • This paper proposes a cooperative parallel tabu search which incorporates with the historical information exchange among processors in addition to its own searching of each processor. We investigate the influence of our proposed cooperative parallel tabu search by comparison with a serial tabu search. We also propose two extensions of the cooperative parallel tabu search which are the cooperative construction of tabu memory and the selection of cooperative partner. Through computational experiment, we observe the improvement of solutions by our proposed method.

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Structural Optimization Using Tabu Search in Discrete Design Space (타부탐색을 이용한 이산설계공간에서의 구조물의 최적설계)

  • Lee, Kwon-Hee;Joo, Won-Sik
    • 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.

Large Scale Unit Commitment Using Parallel Tabu Search (병렬 타부 탐색법을 이용한 대규모의 발전기 기동정지계획)

  • Kim, Hyeong-Su;Mun, Gyeong-Jun;Jo, Deok-Hwan;Hwang, Gi-Hyeon;Park, Jun-Ho
    • 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.

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