Enhanced Approaches to Solving the Multiple Traveling Salesman Problem

2015 ◽  
Author(s):  
Nathan Boone ◽  
Anoop Sathyan ◽  
Kelly Cohen
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multiple Traveling Salesman Problem

Particle Swarm Optimization Combined with Ant Colony Optimization for the Multiple Traveling Salesman Problem

2009 ◽  
Vol 626-627 ◽  
pp. 717-722 ◽  
Author(s):  
Hong Kui Feng ◽  
Jin Song Bao ◽  
Jin Ye
Keyword(s):  
Particle Swarm Optimization ◽  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Particle Swarm ◽  
Traveling Salesman ◽  
Ant Colony ◽  
Great Success ◽  
Swarm Optimization ◽  
Continuous Space ◽  
Multiple Traveling Salesman Problem

A lot of practical problem, such as the scheduling of jobs on multiple parallel production lines and the scheduling of multiple vehicles transporting goods in logistics, can be modeled as the multiple traveling salesman problem (MTSP). Due to the combinatorial complexity of the MTSP, it is necessary to use heuristics to solve the problem, and a discrete particle swarm optimization (DPSO) algorithm is employed in this paper. Particle swarm optimization (PSO) in the continuous space has obtained great success in resolving some minimization problems. But when applying PSO for the MTSP, a difficulty rises, which is to find a suitable mapping between sequence and continuous position of particles in particle swarm optimization. For overcoming this difficulty, PSO is combined with ant colony optimization (ACO), and the mapping between sequence and continuous position of particles is established. To verify the efficiency of the DPSO algorithm, it is used to solve the MTSP and its performance is compared with the ACO and some traditional DPSO algorithms. The computational results show that the proposed DPSO algorithm is efficient.

A Two Stage Method for the Multiple Traveling Salesman Problem

2020 ◽  
Vol 11 (3) ◽  
pp. 79-91
Author(s):  
Azcarie Manuel Cabrera Cuevas ◽  
Jania Astrid Saucedo Martínez ◽  
José Antonio Marmolejo Saucedo
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Difficulty Level ◽  
Median Problem ◽  
Two Stage ◽  
Multiple Traveling Salesman Problem ◽  
Solution Methods ◽  
The Many ◽  
The Traveling Salesman Problem

The variation of the traveling salesman problem (TSP) with multiple salesmen (m-TSP) has been studied for many years resulting in diverse solution methods, both exact and heuristic. However, the high difficulty level on finding optimal (or acceptable) solutions has opposed the many efforts of doing so. The proposed method regards a two stage procedure which implies a modified version of the p-Median Problem (PMP) alongside the TSP, making a partition of the nodes into subsets that will be assigned to each salesman, solving it with Branch & Cut (B&C), in the first stage. This is followed by the routing, applying an Ant Colony Optimization (ACO) metaheuristic algorithm to solve a TSP for each subset of nodes. A case study was reviewed, detailing the positioning of five vehicles in strategic places in the Mexican Republic.

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