caa a22 4500 606158863 CHVBK 20210128100622.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00521-014-1717-7 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1717-7 A similarity-based mechanism to control genetic algorithm and local search hybridization to solve traveling salesman problem [Elektronische Daten] [Marjan Kuchaki Rafsanjani, Sadegh Eskandari, Arsham Borumand Saeid] A big shortcoming of the simple genetic algorithm is that whenever it converges to a local optimum, its performance is continuously deteriorating, especially in the highly nonlinear problems such as traveling salesman problem (TSP). Therefore, some heuristics such as local search are needed to help genetic algorithm (GA) loops escaping such situations. The critical point in such hybridization is the determining a suitable time for applying local search to the GA population. In this study, a new hybridization of GA and local search based on a new similarity-based control mechanism is proposed, and its behavior on different TSP instances is compared with simple GA. The experimental results show that the proposed hybrid algorithm yields the optimal tour length in most of the cases, especially in the TSP instances with higher complexity. The Natural Computing Applications Forum, 2014 Genetic algorithm nationallicence Local search nationallicence Traveling salesman problem nationallicence Similarity-based control nationallicence Kuchaki Rafsanjani Marjan Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran aut Eskandari Sadegh Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran aut Borumand Saeid Arsham Department of Mathematics, Shahid Bahonar University of Kerman, Kerman, Iran aut Neural Computing and Applications Springer London 26/1(2015-01-01), 213-222 0941-0643 26:1<213 2015 26 521 https://doi.org/10.1007/s00521-014-1717-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1717-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Kuchaki Rafsanjani Marjan Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran aut NATIONALLICENCE 700 1- Eskandari Sadegh Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran aut NATIONALLICENCE 700 1- Borumand Saeid Arsham Department of Mathematics, Shahid Bahonar University of Kerman, Kerman, Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/1(2015-01-01), 213-222 0941-0643 26:1<213 2015 26 521