The automatic generation of mutation operators for genetic algorithms

Citation

Woodward J & Swan J (2012) The automatic generation of mutation operators for genetic algorithms. In: GECCO Companion '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion. GECCO Companion '12: Fourteenth international conference on Genetic and evolutionary computation conference companion, Philadelphia, PA, USA, 07.07.2012-11.07.2012. New York, NY: ACM, pp. 67-74. http://dl.acm.org/citation.cfm?id=2330796; https://doi.org/10.1145/2330784.2330796

Abstract
We automatically generate mutation operators for Genetic Algorithms (GA) and tune them to problem instances drawn from a given problem class. By so doing, we perform metalearning in which the base-level contains GAs (which learn about problem instances), and the meta-level contains GAmutation operators (which learn about problem classes). We use Register Machines to explore a constrained design space for mutation operators. We show how two commonly used mutation operators (viz. one-point and uniform mutation) can be expressed in this framework. Iterated local search is used to search the space of mutation operators, and on a test-bed of 7 problem classes we identify machine-designed mutation operators which outperform their human counterparts.

Keywords
Genetic Programming; Genetic Algorithms; Hyper-Heuristics; Automatic Design