%0 Journal Article %1 bennaceur2017genetic %A Bennaceur, Hachemi %A Alanzi, Entesar %D 2017 %J International Journal of Computer Science and Security (IJCSS) %K Algorithm, Constructive Crossover Genetic Optimization Problem, Salesman Sequential Traveling %N 3 %P 42-52 %T Genetic Algorithm For The Travelling Salesman Problem using Enhanced Sequential Constructive Crossover Operator %U http://www.cscjournals.org/library/manuscriptinfo.php?mc=IJCSS-1345 %V 11 %X 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.

@article{bennaceur2017genetic, 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.}, added-at = {2018-12-14T08:38:39.000+0100}, author = {Bennaceur, Hachemi and Alanzi, Entesar}, biburl = {https://www.bibsonomy.org/bibtex/2200d859e201577e7cf72650c744f9a28/cscjournals}, interhash = {f15fb73b23d9244acf178c0fe40eba6f}, intrahash = {200d859e201577e7cf72650c744f9a28}, issn = {1985-1553}, journal = {International Journal of Computer Science and Security (IJCSS)}, keywords = {Algorithm, Constructive Crossover Genetic Optimization Problem, Salesman Sequential Traveling}, language = {English}, month = {June}, number = 3, pages = {42-52}, timestamp = {2018-12-14T08:38:39.000+0100}, title = {Genetic Algorithm For The Travelling Salesman Problem using Enhanced Sequential Constructive Crossover Operator}, url = {http://www.cscjournals.org/library/manuscriptinfo.php?mc=IJCSS-1345}, volume = 11, year = 2017 }