Application of Heuristic Algorithms in the Optimization of Commercial Routes in Real Time
Abstract
The optimization of commercial routes has become of paramount importance for the companies offering this service, seeking to reduce costs, optimize resources, improve the process and satisfy its customers, and contribute to the improvement of urban mobility. This work presents a computational solution for route optimization in real time, using heuristic algorithms for the best path, structured in two modules (web and mobile) connected via web service. The Google Maps API provides geographic information. The solution was used in a real company and gains were identified regarding route optimization.
References
Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA.
Heinen, M. R. and Osório, F. S. (2006) “Algoritmos Genéricos Aplicados ao Problema de Roteamento de Veículos”, In: Revista Hífen, Uruguaiana, v. 30, n. 58.
Monteiro, B. R. and Lisboa Filho, J. (2009) “Sistemas de Informação Geográfica Móveis aplicados no Governo Eletrônico Municipal”, In. I Workshop de Computação Aplicada em Governo Eletrônico WCGE/CSBC. XXIX Congresso da Sociedade Brasileira de Computação. Anais... Porto Alegre. p.1465-1472.
Rodrigues, S. B. (2007) “A Metaheurística Colônia de formigas aplicada a um problema de roteamento de veículos: Caso da Itaipu Binacional”, https://acervodigital.ufpr.br/bitstream/handle/1884/12044/disserta%e7%e3o_samuel_bellido_rodrigues.pdf?sequence=1, Junho 2018.
Tonon, R. (2010) “Cidades Inteligentes”, http://revistagalileu.globo.com/Revista/Common/0,,ERT338454-17773,00.html, Janeiro 2018.
Washburn, D. et al. (2010) “Helping CIOs Understand "Smart City" Initiatives”, http://c3328005.r5.cf0.rackcdn.com/73efa931-0fac-4e28-ae77-8e58ebf74aa6.pdf, Março 2018.
