TY  - JOUR
EP  - 380
SN  - 11343060
PB  - Springer Netherlands
N1  - cited By 76
SP  - 367
TI  - Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem
AV  - none
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034599867&doi=10.1007%2fs11831-017-9247-y&partnerID=40&md5=09f0f0dd53f74be695248768e2e93740
A1  - Halim, A.H.
A1  - Ismail, I.
JF  - Archives of Computational Methods in Engineering
VL  - 26
Y1  - 2019///
IS  - 2
N2  - The Travelling Salesman Problem (TSP) is an NP-hard problem with high number of possible solutions. The complexity increases with the factorial of n nodes in each specific problem. Meta-heuristic algorithms are an optimization algorithm that able to solve TSP problem towards a satisfactory solution. To date, there are many meta-heuristic algorithms introduced in literatures which consist of different philosophies of intensification and diversification. This paper focuses on 6 heuristic algorithms: Nearest Neighbor, Genetic Algorithm, Simulated Annealing, Tabu Search, Ant Colony Optimization and Tree Physiology Optimization. The study in this paper includes comparison of computation, accuracy and convergence. © 2017, CIMNE, Barcelona, Spain.
KW  - Ant colony optimization; Combinatorial optimization; Computational complexity; Genetic algorithms; Nearest neighbor search; Philosophical aspects; Problem solving; Simulated annealing; Tabu search; Traveling salesman problem; Trees (mathematics)
KW  -  Intensification and diversifications; Meta heuristic algorithm; Nearest neighbors; Optimization algorithms; Satisfactory solutions; Specific problems; Travelling salesman problem; Travelling salesman problem (TSP)
KW  -  Heuristic algorithms
ID  - scholars11637
ER  -