群知能と進化的計算の国際ジャーナル

概要

Intelligent System to Emergencies Based on Ant Colony Optimization.

Alberto Ochoa, Julio Ponce, Omar Cano, Paula Hern´andez, J¨ons S´anchez and Ruben Jaramillo

The shortest path problem is a typical problem of optimization. This paper presents the ant colony optimization (ACO) algorithm to solve a problem of routing vehicles in a Fire Department of Leon, Mexico. In this work, diverse components are described to characterize this problem through the use of a bioinspired algorithm. The algorithm was developed in Java, thus obtaining a tool which determines the best tracks to the vehicles. An experiment was realized to probe the validations, the results were used to compare it with Dijkstra algorithm and determine the quality of results. The future work of this research is determine an innovative perspective related to pheromone evaporation and as this topic is determinative to found and remember the best solutions quickly, additionally we compare it with a code from other postgraduate students trying to implement an algorithm similar to Logistics but using a PSO and another with cultural algorithms.