A new genetic algorithm based on dissimilarities and similarities

Marcin Studniarski; Radhwan Al-Jawadi; Aisha Younus

doi:10.7494/csci.2018.19.1.2522

Authors

Marcin Studniarski Faculty of Mathematics and Computer Science, University of Lodz, ul. S. Banacha 22, 90-238 Lodz, Poland
Radhwan Al-Jawadi Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland, (permanent address: Technical College of Mosul, FTE, Iraq), radwanyousif@yahoo.com
Aisha Younus Faculty of Mathematics and Computer Science, University of Lodz, ul. S. Banacha 22, 90-238 Lodz, Poland

DOI:

https://doi.org/10.7494/csci.2018.19.1.2522

Keywords:

Genetic algorithm, Forma analysis, Similarity and dissimilarity of chromosomes, Chromosome injection

Abstract

Optimization is essential for nding suitable answers to real life problems. In particular, genetic (or more generally, evolutionary) algorithms can provide satisfactory approximate solutions to many problems to which exact analytcal results are not accessible. In this paper we present both theoretical and experimental results on a new genetic algorithm called Dissimilarity and Simlarity of Chromosomes (DSC). This methodology constructs new chromosomes starting with the pairs of existing ones by exploring their dissimilarities and similarities. To demonstrate the performance of the algorithm, it is run on 17 two-dimensional, one four-dimensional and two ten-dimensional optimization problems described in the literature, and compared with the well-known GA, CMA-ES and DE algorithms.The results of tests show the superiority of our strategy in the majority of cases.

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