On benchmarking functions for genetic algorithms
نویسندگان
چکیده
This paper presents experimental results on the major benchmarking functions used for performance evaluation of Genetic Algorithms (GAs). Parameters considered include the eect of population size, crossover probability, mutation rate and pseudorandom generator. The general computational behavior of two basic GAs models, the Generational Replacement Model (GRM) and the Steady State Replacement Model (SSRM) is evaluated.
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ورودعنوان ژورنال:
- Int. J. Comput. Math.
دوره 77 شماره
صفحات -
تاریخ انتشار 2001