Publication Type

Conference Proceeding Article

Publication Date

7-2011

Abstract

In this paper, we explore the idea of improving the efficiency of factorial design for parameter tuning of metaheuristics. In a standard full factorial design, the number of runs increases exponentially as the number of parameters. To reduce the parameter search space, one option is to first partition parameters into disjoint categories. While this may be done manually based on user guidance, an automated approach proposed in this paper is to apply a fractional factorial design to partition parameters based on their main effects where each partition is then tuned independently. With a careful choice of fractional design, our approach yields a linear rather than exponential run time performance with respect to the number of parameters. We empirically evaluate our approach for tuning a simulated annealing algorithm that solves an industry spares inventory optimization problem. We show that our proposed methodology leads to improvements in terms of the quality of solutions when compared to a pure application of an automated parameter tuning configurator ParamILS.

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Decision Analytics

Publication

Advances in metaheuristics: Proceedings of the Ninth Meta-heuristics International Conference, Udine, Italy, 25-28 July 2011

Volume

53

First Page

37

Last Page

59

ISBN

9781461463221

Identifier

10.1007/978-1-4614-6322-1_3

Publisher

Springer Verlag

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1007/978-1-4614-6322-1_3