Chapter Seven: Genetic algorithm
Abstract
The focus of this chapter is on a well-known population-based metaheuristic algorithm, called the genetic algorithm (GA). Since the search behavior of GA is inspired by the natural selection theory of Darwin, examples are first given to show the solution structure of GA, that is, what the terms population, chromosome, gene, and fitness mean in GA. Other examples are then given to illustrate the major search operators and the search behavior of GA in the landscape of the solution space. The basic idea and pseudocode of GA are also given to explain the key ideas of fitness values, selection, crossover, and mutation. The source code and simulation results of GA are also presented to show how to use it for ...
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