Development of a new optimization method, yin-yang algorithm, for traveling salesman problem

2011 ◽  
Author(s):  
S.C. Tam ◽  
C.H. Chio ◽  
H.K. Tam
Keyword(s):  
Traveling Salesman Problem ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Yin Yang

A Hybrid Particle Swarm Optimization Method for Traveling Salesman Problem

2017 ◽  
Vol 8 (3) ◽  
pp. 53-65 ◽  
Author(s):  
Yong Wang ◽  
Ning Xu
Keyword(s):  
Particle Swarm Optimization ◽  
Traveling Salesman Problem ◽  
Particle Swarm ◽  
Initial Approximation ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Hamiltonian Circuit ◽  
Swarm Optimization ◽  
Hybrid Particle Swarm Optimization ◽  
Optimal Paths

Traveling salesman problem (TSP) is one well-known NP-Complete problem. The objective is to search the optimal Hamiltonian circuit (OHC) in a tourist map. The particle swarm optimization (PSO) integrated with the four vertices and three lines inequality is introduced to detect the OHC or approximate OHC. The four vertices and three lines inequality is taken as local heuristics to find the local optimal paths composed of four vertices and three lines. Each of this kind of paths in the OHC or approximate OHC conforms to the inequality. The particle swarm optimization is used to search an initial approximation. The four vertices and three lines inequality is applied to convert all the paths in the approximation into the optimal paths. Then a better approximation is obtained. The method is tested with several Euclidean TSP instances. The results show that the much better approximations are searched with the hybrid PSO. The convergence rate is also faster than the traditional PSO under the same preconditions.

scholarly journals PARALLEL TEMPERING FOR THE TRAVELING SALESMAN PROBLEM

2009 ◽  
Vol 20 (04) ◽  
pp. 539-556 ◽  
Author(s):  
CHIAMING WANG ◽  
JEFFREY D. HYMAN ◽  
ALLON PERCUS ◽  
RUSSEL CAFLISCH
Keyword(s):  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Traveling Salesman Problem ◽  
Minimum Distance ◽  
Optimization Problems ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Parallel Tempering ◽  
Combinatorial Optimization Problems ◽  
The Traveling Salesman Problem

We explore the potential of parallel tempering as a combinatorial optimization method, applying it to the traveling salesman problem. We compare simulation results of parallel tempering with a benchmark implementation of simulated annealing, and study how different choices of parameters affect the relative performance of the two methods. We find that a straightforward implementation of parallel tempering can outperform simulated annealing in several crucial respects. When parameters are chosen appropriately, both methods yield close approximation to the actual minimum distance for an instance with 200 nodes. However, parallel tempering yields more consistently accurate results when a series of independent simulations are performed. Our results suggest that parallel tempering might offer a simple but powerful alternative to simulated annealing for combinatorial optimization problems.

Grafos hamiltonianos aplicado al turismo de Panamá

2019 ◽  
Vol 7 (1) ◽  
pp. 109-113
Author(s):  
Julio Trujillo
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman

Un problema clásico de Teoría de Grafos es encontrar un camino que pase por varios puntos, sólo una vez, empezando y terminando en un lugar (camino hamiltoniano). Al agregar la condición de que sea la ruta más corta, el problema se convierte uno de tipo TSP (Traveling Salesman Problem). En este trabajo nos centraremos en un problema de tour turístico por la ciudad de Panamá, transformándolo a un problema de grafo de tal manera que represente la situación planteada.

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