A Kernighan-Lin local improvement heuristic that solves some hard problems in genetic algorithms

Authors:
William A. Greene
Affiliations:
Computer Science Department, University of New Orleans, New Orleans, LA
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Year:
2003

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Abstract

We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heuristic provides very quick solutions to several problems which have been touted in the literature as especially hard ones for genetic algorithms, such as hierarchical deceptive problems. We suggest why the heuristic works well.