用于函數优化的遗传算法的Matlab实现.docVIP

A Genetic Algorithm for Function Optimization: A Matlab Implementation Christopher R. Houck North Carolina State University and Jeffery A. Joines North Carolina State University and Michael G.Kay North Carolina State University Jeffery A. Joines 和Michael G.Kay A genetic algorithm implemented in Matlab is presented. Matlab is used for the following reasons: it provides many built in auxiliary functions useful for function optimization; it is completely portable; and it is efficient for numerical computations. The genetic algorithm toolbox developed is tested on a series of non-linear, multi-modal, non-convex test problems and compared with results using simulated annealing. The genetic algorithm using a foat representation is found to be superior to both a binary genetic algorithm and simulated annealing in terms of effciency and quality of solution. The use of genetic algorithm toolbox as well as the code is introduced in the paper. Categories and Subject Descriptors:G.1[Numerical Analysis]: Optimization--Unconstrained Optimization, nonlinear programming, gradient methods General Terms:Optimization,Algorithms Additional Key Words and Phrases: genetic algorithms, multimodal nonconvex functions,Matlab 1. INTRODUCTION 介绍 Algorithms for function optimization are generally limited to convex regular functions.However,many functions are multi-modal, discontinuous, and nondifferen- ------------------------------------------------------------------------------------------------------------------- Name_ Christopher R.Houck Address:North Carolina State University, Box 7906 Raleigh, NC,27695-7906,USA (919)515-5188,(919)515-1543,chouck@eos.ncsu.edu A ffliation: North Carolina State University Name:Jeffery A. Joines Address: North Carolina State University, Box 7906 Raleigh,NC, 27695-7906,USA (919)515-5188,(919)515-1543,jjoine@eos.ncsu.edu A ffliation:North Carolina State University Name: Michael G.Kay Address: North Carolina State University, Box 7906 Raleigh,NC, 27695-79