Development a new mutation operator to solve the Traveling Salesman Problem by aid of Genetic Algorithms

Authors:
Murat Albayrak;Novruz Allahverdi
Affiliations:
Center Primary Education Scholl, Selki, Huyuk, Konya, Turkey;Electronic and Computer Education Department, Technical Education Faculty, Selcuk University, Konya, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Short communication: Comments on "Albayrak, M., & Allahverdy N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms. Expert Systems with Applications, 38(3), 1313-1320": A proposal of good practice

Expert Systems with Applications: An International Journal

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Abstract

In this study, a new mutation operator has been developed to increase Genetic Algorithm (GA) performance to find the shortest distance in the known Traveling Salesman Problem (TSP). We called this method as Greedy Sub Tour Mutation (GSTM). There exist two different greedy search methods and a component that provides a distortion in this new operator. The developed GSTM operator was tested with simple GA mutation operators in 14 different TSP examples selected from TSPLIB. The application of this GSTM operator gives much more effective results regarding to the best and average error values. The GSTM operator used with simple GAs decreases the best error values according to the other mutation operators with the ratio of between 74.24% and 88.32% and average error values between 59.42% and 79.51%.