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Carnegie Mellon Robotics Institute

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Abstract

"Survival of the fittest" is often seen as the driving force behind adaptation and evolution. For sure, all evolutionary algorithms use fitness-based selection. However, it is not necessary to know where you are, to know where you are going. Similarly, it is not necessary to know the fitness of a solution, to find a better solution. The GENIE algorithm uses random parent selection and a non-elitist generational replacement scheme. Experiments on a non-trivial instance of the Traveling Salesman Problem show that heuristic operators in GENIE can converge to the optimal solution without evaluating fitness.

Keywords

genetic algorithms, commonality hypothesis, Traveling Salesman Problem, 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, Stephen Smith , and Cesar Guerra-Salcedo, "The GENIE is Out! (Who Needs Fitness to Evolve?)," CEC99: Proceedings of the Congress on Evolutionary Computation, 1999.

BibTeX Reference

@inproceedings{Chen_1999_558,
   author = "Stephen Chen and Stephen {Smith } and Cesar Guerra-Salcedo",
   title = "The GENIE is Out! (Who Needs Fitness to Evolve?)",
   booktitle = "CEC99: Proceedings of the Congress on Evolutionary Computation",
   year = "1999",
}

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