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An application of reactive tabu search for service restoration in distribution systems and its comparison with the genetic algorithm and parallel simulated annealing
Author(s) -
Fudo Hiroyuki,
Toune Sakae,
Genji Takamu,
Fukuyama Yoshikazu,
Nakanishi Yosuke
Publication year - 2000
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/1520-6416(20001130)133:3<71::aid-eej9>3.0.co;2-g
Subject(s) - tabu search , simulated annealing , mathematical optimization , genetic algorithm , computer science , combinatorial optimization , algorithm , heuristic , mathematics
Service restoration in distribution systems can be formulated as a combinatorial optimization problem. It is the problem to determine power sources for each load considering various operational constraints in distribution systems. Up to now, the problem has been dealt with using conventional methods such as the branch and bound method, expert systems, neural networks, and fuzzy reasoning. Recently, modern heuristic methods such as genetic algorithms (GA), simulated annealing (SA), and tabu search (TS) have been attracting notice as efficient methods for solving large combinatorial optimization problems. Moreover, reactive tabu search (RTS) can solve the parameter tuning problem, which is recognized as the essential problem of the TS. Therefore, RTS, GA, and SA can be efficient search methods for service restoration in distribution systems. This paper develops an RTS for service restoration and compares RTS, GA, and PSA (parallel SA) for the problem. The feasibility of the proposed methods is shown and compared on a typical distribution system model with promising results. © 2000 Scripta Technica, Electr Eng Jpn, 133(3): 71–82, 2000