New Designs of k-means Clustering and Crossover Operator for Solving Traveling Salesman Problems using Evolutionary Algorithms

Ismail M. Ali, Daryl Essam, Kathryn Kasmarik

2019

Abstract

The traveling salesman problem is a well-known combinatorial optimization problem with permutation-based variables, which has been proven to be an NP-complete problem. Over the last few decades, many evolutionary algorithms have been developed for solving it. In this study, a new design that uses the k-means clustering method, is proposed to be used as a repairing method for the individuals in the initial population. In addition, a new crossover operator is introduced to improve the evolving process of an evolutionary algorithm and hence its performance. To investigate the performance of the proposed mechanism, two popular evolutionary algorithms (genetic algorithm and differential evolution) have been implemented for solving 18 instances of traveling salesman problems and the results have been compared with those obtained from standard versions of GA and DE, and 3 other state-of-the-art algorithms. Results show that the proposed components can significantly improve the performance of EAs while solving TSPs with small, medium and large-sized problems.

Paper Citation

in Harvard Style

Ali I., Essam D. and Kasmarik K. (2019). New Designs of k-means Clustering and Crossover Operator for Solving Traveling Salesman Problems using Evolutionary Algorithms. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA; ISBN 978-989-758-384-1, SciTePress, pages 123-130. DOI: 10.5220/0007940001230130

in Bibtex Style

@conference{ecta19,
author={Ismail M. Ali and Daryl Essam and Kathryn Kasmarik},
title={New Designs of k-means Clustering and Crossover Operator for Solving Traveling Salesman Problems using Evolutionary Algorithms},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA},
year={2019},
pages={123-130},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007940001230130},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA
TI - New Designs of k-means Clustering and Crossover Operator for Solving Traveling Salesman Problems using Evolutionary Algorithms
SN - 978-989-758-384-1
AU - Ali I.
AU - Essam D.
AU - Kasmarik K.
PY - 2019
SP - 123
EP - 130
DO - 10.5220/0007940001230130
PB - SciTePress