Time and Size Limited Harvesting Models of Genetic Algorithm
In this paper we formulate and investigate a novel model of a Genetic Algorithm (GA) in which the genetic population is allowed to grow with a delay in selection. And during selection, the excess growth over a preset constant size is harvested. Two possible delay modes result in two harvesting schemes called time and size limited harvesting. The two schemes generalize the standard genetic algorithm in the direction of treating population size as a stochastic parameter. If the delay threshold is one, then both schemes reduce to the standard genetic algorithm. The retention of low fitness members for extended period in the evolving population promotes preservation of schema pathways which enable escape from local optima and also help alleviate premature convergence. The extended model is successfully applied to a difficult two-dimensional non-stationary problem for tracking time-varying optima in real time.
KeywordsGenetic Algorithm Fitness Landscape Excess Growth Standard Genetic Algorithm Delay Mode
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