Exploring Genetic Algorithm's Selection Approaches: Theory, Implementations and Statistical Analysis

Research output: Book/ReportBookpeer-review

Abstract

Genetic algorithms are optimization search algorithms that maximize or minimizes given functions. Identifying the appropriate selection technique is a critical step in genetic algorithm. The process of selection plays an important role in resolving premature convergence because it occurs due to lack of diversity in the population. Therefore selection of population in each generation is very important. The objective of the research is to investigate the performance of the GA with different selection strategies in terms of minimizing the distance required for covering all the cities in TSP, number of generations required to achieve convergence and execution time to come out with the optimal solution for TSP. Overall, a statistical tests are conducted for the performance significance of the selection strategies.
Original languageEnglish
PublisherScholars' Press
ISBN (Print)978-3-639-76932-6
Publication statusAccepted/In press - 10 Aug 2015

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