A population-based algorithm for the multi travelling salesman problem | Zendy

Rubén Iván Bolaños | Zendy; Eliana Mirledy Toro Ocampo | Zendy; Mauricio Granada Echeverri | Zendy

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A population-based algorithm for the multi travelling salesman problem

Author(s) -

Rubén Iván Bolaños,

Eliana Mirledy Toro Ocampo,

Mauricio Granada Echeverri

Publication year - 2015

Publication title -

international journal of industrial engineering computations

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.564

H-Index - 26

eISSN - 1923-2926

pISSN - 1923-2934

DOI - 10.5267/j.ijiec.2015.10.005

Subject(s) - travelling salesman problem , benchmark (surveying) , mathematical optimization , population , set (abstract data type) , genetic algorithm , algorithm , 2 opt , computer science , quality (philosophy) , mathematics , philosophy , demography , geodesy , epistemology , sociology , programming language , geography

This paper presents the implementation of an efficient modified genetic algorithm for solving the multi-traveling salesman problem (mTSP). The main characteristics of the method are the construction of an initial population of high quality and the implementation of several local search operators which are important in the efficient and effective exploration of promising regions of the solution space. Due to the combinatorial complexity of mTSP, the proposed methodology is especially applicable for real-world problems. The proposed algorithm was tested on a set of six benchmark instances, which have from 76 and 1002 cities to be visited. In all cases, the best known solution was improved. The results are also compared with other existing solutions procedure in the literature

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