Self Controlling Tabu Search algorithm for the Quadratic Assignment Problem

This paper addresses the application of the principles of feedback and self-controlling software to the tabu search algorithm. We introduce two new reaction strategies for the tabu search algorithm. The first strategy treats the tabu search algorithm as a target system to be controlled and uses a co...

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Bibliographic Details
Published in:Computers & industrial engineering Vol. 60; no. 2; pp. 310 - 319
Main Authors: Fescioglu-Unver, Nilgun, Kokar, Mieczyslaw M.
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.03.2011
Pergamon Press Inc
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ISSN:0360-8352, 1879-0550
Online Access:Get full text
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Summary:This paper addresses the application of the principles of feedback and self-controlling software to the tabu search algorithm. We introduce two new reaction strategies for the tabu search algorithm. The first strategy treats the tabu search algorithm as a target system to be controlled and uses a control-theoretic approach to adjust the algorithm parameters that affect search intensification. The second strategy is a flexible diversification strategy which can adjust the algorithm’s parameters based on the search history. These two strategies, combined with tabu search, form the Self Controlling Tabu Search (SC-Tabu) algorithm. The algorithm is implemented and tested on the Quadratic Assignment Problem (QAP). The results show that the self-controlling features of the algorithm make it possible to achieve good performance on different types of QAP instances.
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ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2010.11.014