Parameter Settings for New Generational Genetic Algorithms for Solving Global Optimization Problems
نویسندگان
چکیده
Corresponding Author: Siew Mooi Lim Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Malaysia E-mail: [email protected] Abstract: This study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent.
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عنوان ژورنال:
- JCS
دوره 11 شماره
صفحات -
تاریخ انتشار 2015