Distribution of electric power, multiple traveling salesmen problem, ant colony optimization
This paper presents a methodology to optimize the execution of the commercial services of electric power distribution companies. This activity represents a significant portion of the operational costs of these companies. How to distribute the services to the teams and define efficient routes is a complex problem due to the great number of possible combinations. The set of geographical positions of the services can be seen as an instance of the multiple traveling salesmen problem. We created a variation of the ant colony optimization algorithm to obtain optimized solutions for the distribution of the services and the route of each team. Our methodology was applied to 17 real word instances obtained from an electric power distribution company from the city of Cornélio Procópio, Brazil. Our method obtained an improvement of 42,23% on average when compared to the solutions that were performed in the real world. To allow the reproduction of our results, the source-code of our system and the dataset are freely available at https://github.com/denilsonfag/STACS.
Barbosa, Denilson Fagundes; Silla, Carlos Nascimento Junior; and Kashiwabara, André Yoshiaki, "Applying a variation of the ant colony optimization algorithm to solve the multiple traveling salesmen problem to route the teams of the electric power distribution companies" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 97.