• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1245-1247
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• 1999

This paper describes the optimal reconfiguration of distribution network. The optimal routing of distribution network should provide electricity to customers with quality, and this paper shows that optimal routing of distribution network can be obtained by Neural-Tabu algorithm while keeping constraints such as line power capacity, voltage drop and reliability indices. The Neural-Tabu algorithm is a Tabu algorithm combined with Neural network to find neighborhood solutions. This paper shows that not only the loss cost but also the reliability cost should be considered in distribution network reconfiguration to achieve the optimal routing.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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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.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.843-859
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• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

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

• 한국정보통신학회논문지
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• 제19권5호
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• pp.1084-1090
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• 2015

본 논문에서는 무선 센서 네트워크에서 네트워크의 감시영역을 최대화하기 위해 센서 노드를 효과적으로 배치하는 타부 서치 알고리즘을 제안한다. 무선 센서 네트워크에서 센서 노드의 수가 증가하게 되면 네트워크의 감시영역을 최대화하기 위한 계산량은 급격히 늘어나게 된다. 본 논문에서는 센서 배치 밀도가 높은 네트워크에서 적정한 실행 시간 내에 네트워크의 감시영역을 최대화하는 타부 서치 알고리즘을 제안하며, 효율적인 검색을 위해 타부 서치 알고리즘의 새로운 이웃해 생성 동작을 제안한다. 제안된 알고리즘은 네트워크의 최대 감시영역과 실행속도 관점에서 성능을 평가하며, 평가 결과에서 제안된 알고리즘이 기존의 알고리즘에 비해 성능이 우수함을 보인다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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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.

• 조명전기설비학회논문지
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• 제17권5호
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• pp.80-87
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• 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.

• 한국정보통신학회논문지
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• 제26권8호
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• pp.1196-1204
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• 2022

본 논문은 브로드캐스트 전송방식을 사용하는 무선 애드혹 네트워크에서 네트워크 수명을 최대화하는 최적화 알고리즘을 제안한다. 본 논문에서 제안하는 최적화 알고리즘은 메모리 구조를 이용하여 로컬 검색 방법을 향상시키는 메타휴리스틱 방식인 타부서치 알고리즘을 적용한다. 제안된 타부서치 알고리즘은 네트워크 수명 최대화 문제에 대하여 효율적인 인코딩 방식과 인접해 검색 방법을 제안한다. 제안된 방식을 적용하여 효율적인 브로드캐스트 라우팅을 설계함으로써 전체 네트워크의 수명을 최대화한다. 제안된 타부서치 알고리즘은 네트워크에서 발생하는 브로드캐스트 전송에서 모든 노드의 소모 에너지와 최초 소실 노드 시점, 알고리즘 실행 시간 관점에서 평가되었다. 다양한 조건의 성능평가 결과에서 제안된 타부서치 알고리즘이 이전에 제안된 메타휴리스틱 알고리즘과 비교했을 때 더 우수함을 확인할 수 있었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권5호
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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.