TY - JOUR

T1 - The modification of hybrid method of ant colony optimization, particle swarm optimization and 3-OPT algorithm in traveling salesman problem

AU - Hertono, G. F.

AU - Ubadah,

AU - Handari, B. D.

N1 - Funding Information:
This research is partially funded by Cluster research UI 2015 Grant.
Publisher Copyright:
© 2018 Published under licence by IOP Publishing Ltd.

PY - 2018/3/22

Y1 - 2018/3/22

N2 - The traveling salesman problem (TSP) is a famous problem in finding the shortest tour to visit every vertex exactly once, except the first vertex, given a set of vertices. This paper discusses three modification methods to solve TSP by combining Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and 3-Opt Algorithm. The ACO is used to find the solution of TSP, in which the PSO is implemented to find the best value of parameters α and β that are used in ACO.In order to reduce the total of tour length from the feasible solution obtained by ACO, then the 3-Opt will be used. In the first modification, the 3-Opt is used to reduce the total tour length from the feasible solutions obtained at each iteration, meanwhile, as the second modification, 3-Opt is used to reduce the total tour length from the entire solution obtained at every iteration. In the third modification, 3-Opt is used to reduce the total tour length from different solutions obtained at each iteration. Results are tested using 6 benchmark problems taken from TSPLIB by calculating the relative error to the best known solution as well as the running time. Among those modifications, only the second and third modification give satisfactory results except the second one needs more execution time compare to the third modifications.

AB - The traveling salesman problem (TSP) is a famous problem in finding the shortest tour to visit every vertex exactly once, except the first vertex, given a set of vertices. This paper discusses three modification methods to solve TSP by combining Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and 3-Opt Algorithm. The ACO is used to find the solution of TSP, in which the PSO is implemented to find the best value of parameters α and β that are used in ACO.In order to reduce the total of tour length from the feasible solution obtained by ACO, then the 3-Opt will be used. In the first modification, the 3-Opt is used to reduce the total tour length from the feasible solutions obtained at each iteration, meanwhile, as the second modification, 3-Opt is used to reduce the total tour length from the entire solution obtained at every iteration. In the third modification, 3-Opt is used to reduce the total tour length from different solutions obtained at each iteration. Results are tested using 6 benchmark problems taken from TSPLIB by calculating the relative error to the best known solution as well as the running time. Among those modifications, only the second and third modification give satisfactory results except the second one needs more execution time compare to the third modifications.

UR - http://www.scopus.com/inward/record.url?scp=85045739092&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/974/1/012032

DO - 10.1088/1742-6596/974/1/012032

M3 - Conference article

AN - SCOPUS:85045739092

VL - 974

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012032

T2 - 3rd International Conference on Mathematics: Pure, Applied and Computation, ICoMPAC 2017

Y2 - 1 November 2017 through 1 November 2017

ER -