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 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.

[1]  Alfonsas Misevicius,et al.  A Tabu Search Algorithm for the Quadratic Assignment Problem , 2005, Comput. Optim. Appl..

[2]  Christian Bierwirth,et al.  A search space analysis of the Job Shop Scheduling Problem , 1999, Ann. Oper. Res..

[3]  Éric D. Taillard,et al.  Robust taboo search for the quadratic assignment problem , 1991, Parallel Comput..

[4]  Charles Edward Herring,et al.  Viable Software: the Intelligent Control Paradigm for Adaptable and Adaptive Architecture , 2002 .

[5]  Yixin Diao,et al.  Feedback Control of Computing Systems , 2004 .

[6]  J. K. Lenstra,et al.  Local Search in Combinatorial Optimisation. , 1997 .

[7]  Manuel Laguna,et al.  Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search , 2006, Oper. Res..

[8]  Gene F. Franklin,et al.  Feedback Control of Dynamic Systems , 1986 .

[9]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[10]  Mieczyslaw M. Kokar,et al.  Control theory-based foundations of self-controlling software , 1999, IEEE Intell. Syst..

[11]  R. Laddaga.  Creating robust software through self-adaptation , 1999, IEEE Intelligent Systems and their Applications.

[12]  Alfonsas Misevicius,et al.  An improved hybrid genetic algorithm: new results for the quadratic assignment problem , 2004, Knowl. Based Syst..

[13]  Roberto Battiti,et al.  The Reactive Tabu Search , 1994, INFORMS J. Comput..

[14]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[15]  Zbigniew Michalewicz,et al.  Parameter control in evolutionary algorithms , 1999, IEEE Trans. Evol. Comput..

[16]  Charles Fleurent,et al.  Genetic Hybrids for the Quadratic Assignment Problem , 1993, Quadratic Assignment and Related Problems.

[17]  É. Taillard.  COMPARISON OF ITERATIVE SEARCHES FOR THE QUADRATIC ASSIGNMENT PROBLEM. , 1995 .

[18]  Fred Glover,et al.  Artificial intelligence, heuristic frameworks and tabu search , 1990 .

[19]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[20]  Mieczyslaw M. Kokar,et al.  An architecture for software that adapts to changes in requirements , 2000, J. Syst. Softw..

[21]  Kai-Yuan Cai,et al.  An Overview of Software Cybernetics , 2003, STEP.

[22]  Mieczyslaw M. Kokar,et al.  An experiment in using control techniques in software engineering , 1997, Proceedings of 12th IEEE International Symposium on Intelligent Control.

[23]  Edward P. K. Tsang,et al.  Guided local search and its application to the traveling salesman problem , 1999, Eur. J. Oper. Res..

[24]  Kevin Leyton-Brown,et al.  Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms , 2006, CP.

[25]  Xiaoyun Zhu,et al.  Utilization and SLO-Based Control for Dynamic Sizing of Resource Partitions , 2005, DSOM.

[26]  Andy Laws,et al.  Model-Based Self-Managing Systems Engineering , 2005, 16th International Workshop on Database and Expert Systems Applications (DEXA'05).

[27]  Xiaoyun Zhu,et al.  Utility-driven workload management using nested control design , 2006, 2006 American Control Conference.

[28]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[29]  Thomas Stützle,et al.  A Racing Algorithm for Configuring Metaheuristics , 2002, GECCO.

[30]  Teofilo F. Gonzalez,et al.  P-Complete Approximation Problems , 1976, J. ACM.

[31]  Robert Laddaga,et al.  The GRAVA self-adaptive architecture: history; design; applications; and challenges , 2004, 24th International Conference on Distributed Computing Systems Workshops, 2004. Proceedings..

[32]  Steve Y. Chiu,et al.  Fine-tuning a tabu search algorithm with statistical tests , 1998 .

[33]  S. Beer.  The Brain of the Firm , 1972 .

[34]  Zvi Drezner,et al.  The extended concentric tabu for the quadratic assignment problem , 2005, Eur. J. Oper. Res..

[35]  S. E. Karisch,et al.  QAPLIB-A quadratic assignment problem library , 1991 .

[36]  Holger H. Hoos,et al.  An adaptive noise mechanism for walkSAT , 2002, AAAI/IAAI.