Multi-objective traveling salesman problem: an ABC approach

2020 ◽  
Vol 50 (11) ◽  
pp. 3942-3960
Author(s):  
Indadul Khan ◽  
Manas Kumar Maiti ◽  
Krishnendu Basuli
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Objective

scholarly journals Algorithm for Multi- objective Traveling Salesman Problems based on Modified Transitive closure

2019 ◽  
Vol 9 (2) ◽  
pp. 2576-2581 ◽  
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Transitive Closure ◽  
Traveling Salesman ◽  
Traveling Salesman Problems ◽  
Numerical Examples ◽  
Multi Objective ◽  
Closure Method ◽  
Closure Algorithm

One of the challenging facts of the Multi Objective Traveling Salesman Problem (MOTSP) is to find the best compromised solution. In this paper, we have proposed a modified transitive closure algorithm to solve MOTSP using Genetic Algorithm (GA). Modified Transitive Closure method generates all the initial solutions of each objective. By applying Genetic Algorithm (GA), compromised solutions are obtained. Numerical examples are provided to show the efficiency of the proposed algorithm for MOTSP

scholarly journals A Multi-objective Version of the Lin-Kernighan Heuristic for the Traveling Salesman Problem

2018 ◽  
Vol 25 (1) ◽  
pp. 48
Author(s):  
Emerson Bezerra De Carvalho ◽  
Elizabeth Ferreira Gouvêa Goldbarg ◽  
Marco Cesar Goldbarg
Keyword(s):  
Local Search ◽  
Traveling Salesman Problem ◽  
State Of The Art ◽  
Symmetric Case ◽  
Traveling Salesman ◽  
Weighted Sum ◽  
Pareto Dominance ◽  
Multi Objective ◽  
The Traveling Salesman Problem ◽  
Single Objective

The Lin and Kernighan’s algorithm for the single objective Traveling Salesman Problem (TSP) is one of the most efficient heuristics for the symmetric case. Although many algorithms for the TSP were extended to the multi-objective version of the problem (MTSP), the Lin and Kernighan’s algorithm was still not fully explored. Works that applied the Lin and Kernighan’s algorithm for the MTSP were driven to weighted sum versions of the problem. We investigate the LK from a Pareto dominance perspective. The multi-objective LK was implemented within two local search schemes and applied to 2 to 4-objective instances. The results  showed that the proposed algorithmic variants obtained better results than a state-of-the-art algorithm.

Sign in / Sign up

Export Citation Format

Share Document