• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.80-87
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• 2003

Network reconfiguration in distribution systems is realized by changing the status of sectiona1izing switches, and is usually done for loss minimization or load balancing in the system This parer presents an approach for loss minization in distribution systems using reactive tabu search. Tabu search attempts to determine a better solution in the manner of a greatest-descent algorithm, but it can not give any guarantee for the convergence property. Reactive tabu search can give convergence property by using reaction and escape mechanism. Therefore, it can find global optimal solution regardless of initial system configuration. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the 32 bus system models.

• 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.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.465-466
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• 2007

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. 본 연구에서는 RTS의 reaction과 escape 매커니즘 구현을 위하여 해싱 함수를 이용하였고 또한 제시된 방식을 32모선에 적용, 기존의 참고문헌과 비교함으로써 그 유용성을 입증하였다.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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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.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.467-477
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• 2001

반응적 타부 탐색은 단순한 타부 탐색과 비교해서 중장기 메모리를 이용한 학습을 통하여 타부리스트의 크기를 반응적으로 변화시킴으로써 NP-hard 문제에 속하는 다양한 조합 최적해 문제에 대해서 좋은 해를 효율적으로 찾는다. 본 논문에서는 반응적 타부 탐색에 있어서 중장기 메모리를 이용한 탈출 메커니즘으로 이웃 해 전략 전환 메커니즘이라는 개념을 제시한다. 제시된 이웃 해 전략 전환 메커니즘을 이용한 반응적 타부 탐색을 특정 공과 대학의 강의 시간표 작성 문제와 외판원문제 (traveling salesman problem)에 적용하여 기존의 반응적 타부 탐색과 비교 분석을 하였다. 전산 실험 결과 제시된 알고리즘은 기존의 반응적 타부 탐색 알고리즘에 비교하여 더 좋은 해를 더 짧은 시간에 찾아주었다.