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Carnegie Mellon Robotics Institute

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Abstract

The Commonality-Based Crossover Framework defines crossover as a two-step process: 1) preserve the maximal common schema of two parents, and 2) complete the solution with a construction heuristic. In these "heuristic" oper ators, the first step is a form of selection. This commonality-based form of selection has been isolated in GENIE. Using random parent selection and a non-elitist generational replacement scheme, GENIE does not include fitness-based selection. However, a theoretical analysis shows that "ideal" construction heuristics in GENIE can potentially converge to optimal solutions. Experimentally, results show that the effectiveness of practical construction heuristics can be amplified by commonality- based restarts. Overall, it is shown that the commonality hypothesis is valid--schemata common to above-average solutions are indeed above average. Since common schemata can only be identified by multi-parent operators, commonality-based selection is a unique advantage that crossover can enjoy over mutation.

Keywords

genetic algorithms, Traveling Salesman Problem, commonality hypothesis, heuristic amplification

Notes

Associated Center(s) / Consortia: Center for Integrated Manfacturing Decision Systems

Associated Lab(s) / Group(s): Intelligent Coordination and Logistics Laboratory

Text Reference

Stephen Chen and Stephen Smith , "Introducing a New Advantage of Crossover: Commonality-Based Selection," GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference, 1999.

BibTeX Reference

@inproceedings{Chen_1999_555,
   author = "Stephen Chen and Stephen {Smith }",
   title = "Introducing a New Advantage of Crossover: Commonality-Based Selection",
   booktitle = "GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference",
   publisher = "Morgan Kaufmann",
   year = "1999",
}

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