• 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.

• 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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.135-138
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• 1996

In solving the Travel Salesman Problem(TSP), we easily reach local optimal solutions with the existing methods such as TWO-OPT, THREE-OPT, and Lin-Kernighen. Tabu search, as a meta heuristic, is a good mechanism to get an optimal or a near optimal solution escaping from the local optimal. By utilizing AI concepts, tabu search continues to search for improved solutions. In this study, we focus on developing a new neighborhood structure that maintains the feasibility of the tours created by exchange operations in TSP. Intelligent methods are discussed, which keeps feasible tour routes even after exchanging several edges continuously. An extended tabu search model, performing cycle detection and diversification with memory structure, is applied to TSP. The model uses effectively the information gathered during the search process. Finally, the results of tabu search and simulated annealing are compared based on the TSP problems in the prior literatures.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.377-381
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• 2003

The design of speed controller for induction motor using tabu search is studied. The proposed sensorless vector control for Induction Motor is composed of two parts. The first part is for optimizing the initial parameters of input-output. The second part is for real time changing parameters of input-output using tabu search. Proposed tabu search is improved by neighbor solution creation using Gaussian random distribution. In order to show the usefulness of the proposed method, we apply the proposed controller to the sensorless speed control of an actual AC induction Motor System. The performance of this approach is verified through simulation.

• 산업경영시스템학회지
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• 제23권60호
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• pp.67-72
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• 2000

In this paper we consider to parallel machines scheduling problems for minimizing mean tardiness that is known NP-complete. This problems is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. A Tabu Search method is applied to the problems considered in this paper to get an improved solution. To this end, we design move attribute, Tabu attribute and Tabu tenure, and thereafter perform the experiments to the problems.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• 한국산학기술학회논문지
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• 제9권6호
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• pp.1838-1855
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• 2008

생산 공정의 효율화는 모든 제조 산업이 추구하고 있는 목표이다. 본 논문에서는 다양한 타입의 제품을 병렬기계에 투입 할 때 목표한 품질을 만족시키고 동시에 평균 납기지연 시간을 최소화 하는 효율적인 작업투입방법에 대하여 기술하였다. 본 연구에서는 품질을 고려하고 실시간으로 작업을 투입해야 하는 공정에서 Rolling Horizon 타부탐색(Tabu search)방법을 이용하여 평균 납기 지연시간을 최소화 하는 방안을 개발하였다. 시뮬레이션을 통해 제안하는 방법의 효율성을 비교대안과 비교하였다. 본 방법은 실제 생산 공정에서 품질과 납기를 동시에 만족 시킬 수있는 효율적인 작업투입 방법으로 사용되어 기업의 수익향상과 신뢰성 확보를 이룰 수 있다.

• Journal of Magnetics
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• 제20권2호
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• pp.161-165
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• 2015

The Permanent Magnet Brushless DC (PMBLDC) motors have been used in modern industrial factories, hazardous chemical process, modern medical devices, and especially in advanced military devices such as army drones. By considering their sensitive role in the industrial and military applications, their optimal design has a real concern. This paper proposes a method for optimal eco-design of a PMBLDC motor using improved tabu search optimization. The objective function is based on losses, volume and cost. Electrical and mechanical requirements and other limitations are combined into constraints of problem. Also, finite element analysis has been used for verifications in magnetic mode.

• 한국수자원학회논문집
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• 제38권9호
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• pp.761-770
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• 2005

본 연구에서는 퍼지논리제어의 적용을 통해 홍수시 저수지의 방류량을 결정하는데 있어, 예측유입량 자료에 내재된 불확실성을 고려할 수 있는 저수지 운영 모형을 구성하고자 하였다. 제어규칙은 전문가들의 의견을 반영해 규칙기반을 설정하는데 이러한 일반적인 방법의 단점을 보완하고자 전역 최적화 기법인 타부탐색을 이용하여 제어규칙을 자동적으로 설정해 퍼지-타부탐색 모형을 구성하였다. 모형의 적용 결과, 첨두방류량이 감소되어 홍수조절율이 개선되었으며, 총 방류량도 감소하는 것으로 나타나 결과적으로 치수효과가 증대될 수 있음을 확인하였다. 또한 홍수 후에 가용할 수 있는 수자원의 양이 증가되어 실제운영방법보다 이수적 차원에서 향상된 결과를 나타내었다.

• 한국정보통신학회논문지
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• 제13권12호
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• pp.2625-2632
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• 2009

최근 효율적인 유도전동기 운전은 벡터제어에 의해 고성능 산업응용 분야에 쓰이고 있으며, 전동기 회전속도를 검출하기 위해 속도센서를 모터에 부착한다. 그러나 속도센서가 있으므로 나타나는 단점인 전기적 노이즈 발생을 최소화하도록 케이블 배치를 하여야 하며, 견고성이 떨어지고, 가격이 상승하는 등 단점이 많아 속도 센서가 없는 속도센서리스 벡터제어 이론에 대한 연구가 진행되어 왔다. 본 연구에서는 타부 탐색을 이용한 유도전동기의 센서리스 벡터제어기를 연구하였다. 제안된 유도전동기 센서리스 벡터제어기는 두 부분으로 구성되어 있다. 첫 번째 부분은 타부 탐색법을 이용하여 첫 번째는 속도 추정기 초기 PI 게인 파라미터를 최적화 하는 부분이며, 두 번째 부분은 속도 제어기 PI 게인 파라미터를 최적화 시키는 부분이다. 제안된 타부 탐색법은 이웃해 영역을 찾는 방법을 삼각형 랜덤 분포를 이용하여 탐색 성능을 향상 시켰다. 제안된 방법을 유도 전동기 센서리스 벡터제어기에 적용하였고 성능을 시뮬레이션과 실험으로 검증하였다. 그 결과 부하의 변동에도 안정적으로 동작하였으며 유용성을 입증하였다.