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Genetic Algorithm For The Travelling Salesman Problem using Enhanced Sequential Constructive Crossover Operator
Hachemi Bennaceur, Entesar Alanzi
Pages - 42 - 52     |    Revised - 31-05-2017     |    Published - 30-06-2017
Volume - 11   Issue - 3    |    Publication Date - June 2017  Table of Contents
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KEYWORDS
Traveling Salesman Problem, Optimization Problem, Genetic Algorithm, Sequential Constructive Crossover.
ABSTRACT
Traveling Salesman Problem (TSP) is one of the most important combinatorial optimization problems. There are many researches to improve the genetic algorithm for solving TSP. The Sequential Constructive crossover (SCX) is one of the most efficient crossover operators for solving optimization problems. In this paper, we propose a new crossover operator, named Enhanced Sequential Constructive crossover operator (ESCX), which modifies and improves the criteria of SCX operator in construction of offspring. ESCX considers, in addition to the real cost of the traversed cities, an estimation cost of the remaining tour, and it selects the next node to build the offspring based on that evaluation. The experimental results comparing the proposed crossover operator to the SCX operator on some benchmark TSPLIB instances show the effectiveness of our proposed operator.
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Professor Hachemi Bennaceur
Faculty of Computer and Information Sciences Department of Computer Science Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia - Saudi Arabia
hamnasser@imamu.edu.sa
Mr. Entesar Alanzi
Department of Computer Science Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia - Saudi Arabia