Informed operators: speeding up genetic-algorithm-based design optimization using reduced models
作者： Khaled Rasheed , Haym Hirsh
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摘要: In this paper we describe a method for improving genetic-algorithm-based optimization using informed genetic operators. The idea is to make the operators such as mutation and crossover more reduced models. every place where random choice made, example when point mutated, instead of generating just one generate several, rank them model, then take best be result mutation. proposed particularly suitable search spaces with expensive evaluation functions, arise in engineering design. Empirical results several design domains demonstrate that can significantly speed up GA optimizer.
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