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IMI/Publicaţii/CSJM/Ediţii/CSJM v.27, n.3 (81), 2019/

A new multi-offspring crossover operator for genetic algorithm to facilitate the traveling salesman problem

Authors: Abid Hussain, Salman A. Cheema
Keywords: Traveling salesman problem, genetic algorithms, crossover operators, multi-offspring, performance index.

Abstract

This research work provides a detailed working principle and official analysis of a multi-offspring crossover operator. The pro- posed operator explains the true theory of survival-of-fittest using the foundation of evolutionary theories of biology and ecological theories of mathematics. We found a considerable improvement because the proposed operator enhances the opportunity of hav- ing better offspring, which results in highly competitive popu- lation. Simulation results of this operator with other competi- tor crossover operators for one of the combinatorial optimization problems, i.e. traveling salesman problem, are obviously showing its pros at better accuracy level. Moreover, the t-test and per- formance index (PI) establishes the improved significance and accuracy levels of the proposed operator. Preferable results of this operator not only confirm its advantages over the others, but also show long run survival of a generation having a number of offspring more than the number of parents with the help of mathematical ecology theory.

Abid Hussain
Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
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Salman A. Cheema
School of Mathematical and Physical Sciences, University of Newcastle, Australia
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