Tournament selection mechanism based random vector selection in differential evolution algorithm

Et Al Abbas

doi:10.21833/ijaas.2017.07.022

Abstract

Tournament selection mechanism based random vector selection in differential evolution algorithm

Highlights

Differential Evolution (DE) is a simple, powerful and easy to use global optimization algorithm
For each random vector used in the equation of the variants, a tsrvde vector will be generated by using the criteria of tournament selection
Result of each DE mutation strategy and its corresponding TSRVDE strategy are shown as a pair under binomial and exponential schemes

Summary

Introduction

Algorithm trial vector of each population member is generated by summing the amplified weighted difference of two vectors to another vector (De Oliveira and Saramago, 2008). Piotrowski and Napiorkowski (2010) have proposed grouping based DE (GDE) algorithm in their research work They have divided the population into four groups where three groups communicate rarely and fourth one communicate with all groups to obtain to keep it updated from the current population knowledge during the search process. Mininno et al (2011) have introduced statistic description based Compact Differential Evolution (cDE) in their research work This algorithm processes the statistic description of population that makes it capable to perform efficiently. Cai and Wang (2013) have introduced neighborhood and direction information based DE algorithm in their research work. This proposed version is composed of two operators for selection and mutation. Various state-of-the-art DE algorithms versions like FADE (Liu and Lampinen, 2005), jDE (Brest et al, 2006), ADE (Zaharie, 2003), JADE (Zhang and Sanderson, 2009), SaDE (Qin et al, 2009), DEGL (Das et al, 2009), CoDE (Wang et al, 2011) ,EPSDE (Mallipeddi et al, 2011), MDE_pBX (Islam et al, 2012), etc. are based on adaption / selection of parameters as well as adaption / selection of mutation strategies mechanisms

Mutation

Selection

Test functions and experimental results

Conclusion and future work