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The New Crossover Operator of Genetic Algorithm for Solving the Traveling Salesman Problem

عنوان مقاله: The New Crossover Operator of Genetic Algorithm for Solving the Traveling Salesman Problem
شناسه ملی مقاله: MHAA02_011
منتشر شده در دومین کنفرانس ملی الگوریتم‌های فراابتکاری و کاربردهای آن در علوم و مهندسی در سال 1396
مشخصات نویسندگان مقاله:

Fatemeh khezerlou - Graduate Student of Artificial Intelligence, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz,Iran,

خلاصه مقاله:
In this paper, designed and implemented a proposed method that is able to obtain an optimal solution to Traveling Salesman Problem (TSP) from a huge search space. This proposed method is based the use of Genetic Algorithm. The algorithm employs a roulette wheel based selection mechanism and also use of Elitism strategy, a proposed local intelligent crossover operator, and an Inversion mutation operator.To illustrate it more clearly, a program based on this algorithm has been implemented. The proposed operator was tested and compared with other crossover operators, such as Position Base, Partially Mapped and Order crossover operators. The results showed that the proposed operator has the best results with minimum distance which was 721.2900 when the system has been applied for solving TSP of 50 cities

کلمات کلیدی:
Traveling Salesman Problem, Genetic Algorithm, selection operator, intelligent crossover operator

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/655911/