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Self Controlling Tabu Search algorithm for the Quadratic Assignment Problem
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DOI：10.1016/j.cie.2010.11.014.png)
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Abstract
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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. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords:
Self-controlling software
Tabu search
Reactive search
Quadratic Assignment Problem
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