Self Controlling Tabu Search algorithm for the Quadratic Assignment Problem

Authors:
Nilgun Fescioglu-Unver;Mieczyslaw M. Kokar
Affiliations:
Department of Industrial Engineering, TOBB University of Economics and Technology, Ankara, Turkey;Electrical and Computer Engineering Department, Northeastern University, Boston, MA, USA
Venue:
Computers and Industrial Engineering
Year:
2011

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Abstract

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.