• 한국지능시스템학회논문지
• /
• 제8권3호
• /
• pp.71-79
• /
• 1998

본 논문은 유전알고리즘과 random tabu 탐색법을 조합한 새로운 최적화 알고리즘을 제안한다. 유전알고리즘과 전역적인 최적해에 대한 탐색능력이 우수하고, random tabu 탐색법은 최적해에의 수렴속도가 매우 빠른 알고리즘이다. 본 논문에서는 이 두 알고리즘의 장점을 이용해서 수렴정도와 수렴속도가 더욱 향상된 최적알고리즘을 제안하여 알고리즘의 수렴성능을 조사하고, 실제 최적화문제로서 지진응답을 최소로 하기위한 배관지지대의 최적배치문제에 적용하여 기존의 방법과 비교를 통하여 유용성을 검토하였다.

• 대한기계학회논문집A
• /
• 제27권5호
• /
• pp.798-806
• /
• 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.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 1997년도 추계학술대회논문집; 한국과학기술회관; 6 Nov. 1997
• /
• pp.184-189
• /
• 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.

• 대한전기학회논문지:전력기술부문A
• /
• 제50권2호
• /
• pp.76-82
• /
• 2001

This paper presents a approach for a service restoration and optimal reconfiguration of distribution network using Genetic algorithm(GA) and Tabu search(TS) method. Restoration and reconfiguration problems in distribution network are difficult to solve in short times, because distribution network supplies power for customers combined with many tie-line switches and sectionalizing switches. Furthermore, the solutions of these problems have to satisfy radial operation conditions and reliability indices. To overcome these time consuming and sub-optimal problem characteristics, this paper applied Genetic-Tabu algorithm. The Genetic-Tabu algorithm is a Tabu search combined with Genetic algorithm to complement the weak points of each algorithm. The case studies with 7 bus distribution network showed that not the loss reduction but also the reliability cost should be considered to achieve the economic service restoration and reconfiguration in the distribution network. The results of suggested Genetic-Tabu algorithm and simple Genetic algorithm are compared in the case study also.

• 정보통신설비학회논문지
• /
• 제10권4호
• /
• pp.128-134
• /
• 2011

Note that k-anonymity algorithm has been widely discussed in the area of privacy protection. In this paper, a new search algorithm to achieve k-anonymity for database application is introduced. A lattice is introduced to form a solution space for a k-anonymity problem and then a hybrid search method composed of tabu search and genetic algorithm is proposed. In this algorithm, the tabu search plays the role of mutation in the genetic algorithm. The hybrid method with independent tabu search and genetic algorithm is compared, and the hybrid approach performs the best in average case.

• 조명전기설비학회논문지
• /
• 제17권5호
• /
• pp.80-87
• /
• 2003

본 논문은 경험적인 탐색방법인 Reactive Tabu Search를 배전계통의 최적 재구성에 적용하였다. 일반적으로 Tabu search는 기울기가 감소하는 방향으로 탐색을 하기 때문에 적은 계산 시간으로 좋은 해를 얻을 수 있지만 초기의 계통 구성에 따라 수렴의 특성이 좌우되어 전역적인 최소해를 찾기가 어려운 단점이 있다 반면 RTS(Reactive Tabu search)는 reaction과 escape 메커니즘을 제공함으로써 파라미터 선정을 자동적으로 적응시키는 것이 가능하여 계통의 초기 구성에 관계 없이 전역적인 해를 적은 계산량으로도 찾을 수 있다. 렬 연구에서는 RTS의 reaction과 escape메커니즘 구현을 위하여 해싱 함수를 이용하였고 또한 제시된 방식을 32모선에 적용, 기존의 참고문헌과 비교함으로써 그 유용성을 입증하였다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권5호
• /
• pp.323-330
• /
• 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.

• 산업공학
• /
• 제17권spc호
• /
• pp.97-102
• /
• 2004

AGV flowpath layout design is one of the most important steps for efficient AGV systems design. Since it was formulated by Gaskins & Tanchoco (1987), a unidirectional AGV flowpath layout design problem has been tackled by many researchers. However, the solution methods were traded off between the solution quality and the computational time. In this paper, a tabu search technique is applied to obtain a good solution for a relatively large problem in reasonable computational time. Specifically, fast construction algorithm for feasible initial solutions, long-term memory structure and neighbor solutions generation are adapted to the problem characteristics and embedded in the tabu search algorithm. Also, sets of computational experiments show that the proposed tabu search algorithm outperforms to the Ko and Egbelu's algorithm (2003).

• Journal of Advanced Marine Engineering and Technology
• /
• 제40권2호
• /
• pp.138-145
• /
• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• 산업경영시스템학회지
• /
• 제18권35호
• /
• pp.107-114
• /
• 1995

This paper proposes the Tabu Search algorithm to minimize mean tardiness in the parallel machine scheduling problem. The algorithm reduces the computation time by employing restricted neighborhood and produces an efficient solution in this problem.