Meta-Heuristic Algorithm based on Ant Colony Optimization Algorithm and Project Scheduling Problem (PSP) for the Traveling Salesman Problem

Authors

  • Fuentes-Penna Alejandro Escuela Superior de Tlahuelilpan – Universidad Autónoma del Estado de Hidalgo (ESTl – UAEM)
  • González-Ramírez Marcos S. 2Universidad Autónoma del Estado de Morelos

Keywords:

Project Scheduling Problem, Ant Colony Optimization, Traveling Salesman Problem, Scheduling Project Ant Colony Optimization

Abstract

The main target of Traveling Salesman Problem (TSP) is to construct the path with the lowest time between different cities, visiting every one once. The Scheduling Project Ant Colony Optimization (SPANCO) Algorithm proposes a way to solve TSP problems adding three aspects: time, cost effort and scope, where the scope is the number of cities, the effort is calculated multiplying time, distance and delivering weight factors and dividing by the sum of them and optimizing the best way to visit the cities graph.

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Published

2013-04-01

How to Cite

Fuentes-Penna Alejandro, & González-Ramírez Marcos S. (2013). Meta-Heuristic Algorithm based on Ant Colony Optimization Algorithm and Project Scheduling Problem (PSP) for the Traveling Salesman Problem. Journal of Network and Innovative Computing, 1, 10. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/27

Issue

Vol. 1 (2013)

Section

Original Article

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