Performance comparison of sequential and parallel execution of the Ant Colony Optimization algorithm for solving the traveling salesman problem

Author

Fejzagic, Elmedina ; Oputic, Adna

Author_Institution

Fac. of Electr. Eng., Univ. of Sarajevo, Sarajevo, Bosnia-Herzegovina

fYear

2013

fDate

20-24 May 2013

Firstpage

1301

Lastpage

1305

Abstract

Ant Colony Optimization (ACO) is a metaheuristic algorithm which uses ideas from nature to find solutions to instances of the Travelling Salesman Problem (TSP) and other combinatorial optimisation problems. ACO is taken as one of the high performance computing methods for TSP. In this paper, the impact of parallelizing an ant colony optimization (ACO) algorithm for the traveling salesman problem in increasing performances is studied, using the task parallel library. One of the main reasons for parallelizing this alghoritm is to reduce the time needed to find a solution while the quality of solution is the same as in the algorithm which is not parallelized.

Keywords

ant colony optimisation; parallel algorithms; travelling salesman problems; ACO; TSP; ant colony optimization algorithm parallelization; combinatorial optimisation problems; high performance computing methods; metaheuristic algorithm; parallel execution; performance comparison; sequential execution; task parallel library; traveling salesman problem; Algorithm design and analysis; Ant colony optimization; Cities and towns; Libraries; Optimization; Parallel processing; Traveling salesman problems; ant colony optimization; parallelization; travelling salesman problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Information & Communication Technology Electronics & Microelectronics (MIPRO), 2013 36th International Convention on

Conference_Location

Opatija

Print_ISBN

978-953-233-076-2

Type

conf

Filename

6596460