PLANEJAMENTO DE ROTAS ÓTIMAS COM ALGORITMOS GENÉTICOS:

UMA SOLUÇÃO PARA A OTIMIZAÇÃO DE TRANSPORTE

Authors

  • Matheus Costa Pereira Universidade Federal de Itajubá - Unifei
  • Anderson Paulo de Paiva Universidade Federal de Itajubá - Unifei
  • Vinícius Antônio Montgomery de Miranda Universidade Federal de Itajubá - Unifei
  • Pedro Jose Papandrea Brasil Educação S/A https://orcid.org/0000-0001-7614-253X

Keywords:

Routing, Optimization, Genetic Algorithms

Abstract

The transportation of goods by roads accounts for a significant volume of freight movement in Brazil, which necessitates making informed decisions in this sector. In this context, a study was conducted to address the Transportation Problem and apply Operations Research (OR) with the aim of optimizing routes to maximize profits and minimize expenses, distance traveled, and travel time. The article describes the stages of this study, from problem identification and software development to the analysis of a routing case using genetic algorithms. The routing tool is a vital instrument for optimizing transportation routes as it seeks to find the most efficient sequence of points. It was created and programmed using Visual Basic for Applications (VBA) and integrated with My Maps to display real maps, with the purpose of providing effective contributions to companies.

Author Biography

Pedro Jose Papandrea, Brasil Educação S/A

Post-Doctorate PDJ CNPq, Ph.D. in Production Engineering from the Federal University of Itajubá and University of Tennessee (University of Tennessee, Knoxville), USA in the PDSE CAPES modality (2018). Master in Production Engineering from the Federal University of Itajubá (2013). Post-graduated in Production Engineering from the Federal University of Itajubá in Quality and Productivity (2011). Bachelor of Business Administration from the Faculty of Administration and Informatics of Santa Rita do Sapucaí (2005). Professor and consultant in Production Engineering and Business Administration. Black Belt Lean Six Sigma. Bachelor of Science in Accounting from Universidade Cidade de São Paulo (SP). Graduating in Industrial Production Management from the University of the City of São Paulo (SP).

References

BALLOU, Ronald H. Gerenciamento da Cadeia de Suprimentos: Logística Empresarial. Porto Alegre: Bookman editora, 2007.

BOWERSOX, Donald J.; CLOSS, David J. Logística empresarial: o processo de integração da cadeia de suprimento. 2007. p. 594-594.

CHING, Hong Yuh. Gestão de estoques na cadeia de logística integrada-supply chain. Editora Atlas SA, 2000.

CLARENS, Gérard C.; HURDLE, V. F. An operating strategy for a commuter bus system. Transportation Science, v. 9, n. 1, p. 1-20, 1975.

CONFEDERAÇÃO NACIONAL DO TRANSPORTE – CNT. Perfil Empresarial 2021: Transporte Rodoviário de Cargas. Brasília: CNT, 2021.

DE OLIVEIRA, Lucas Guedes et al. Response surface methodology for advanced manufacturing technology optimization: theoretical fundamentals, practical guidelines, and survey literature review. The International Journal of Advanced Manufacturing Technology, v. 104, p. 1785-1837, 2019.

JÜNGER, Michael; REINELT, Gerhard; RINALDI, Giovanni. The traveling salesman problem. Handbooks in operations research and management science, v. 7, p. 225-330, 1995.

KARP, Richard M. On the computational complexity of combinatorial problems. Networks, v. 5, n. 1, p. 45-68, 1975.

KOTHARI, Chakravanti Rajagopalachari. Research methodology: Methods and Techniques. 2ª ed. New Age International Publishers, 2004.

MERZ, P. Memetic algorithms for combinatorial optimization problems: Fitness landscapes and effective search strategies, Ph.D. Theses, Parallel Systems Research Group. Department of Electrical Engineering and Computer Science. University of Siegen, 2000.

NISSEN, Volker; BIETHAHN, Jörg. An introduction to evolutionary algorithms. Evolutionary algorithms in management applications, p. 3-43, 1995.

SEGUY, Vivien et al. Large-scale optimal transport and mapping estimation. 6th International Conference on Learning Representations, ICLR, 2018.

TAHA, Hamdy A. Operations research: an introduction. Journal of Manufacturing Systems, v. 1, n. 17, p. 78, 1998.

Additional Files

Published

2024-01-12

How to Cite

Costa Pereira, M., de Paiva, A. P., Montgomery de Miranda, V. A., & Papandrea, P. J. (2024). PLANEJAMENTO DE ROTAS ÓTIMAS COM ALGORITMOS GENÉTICOS:: UMA SOLUÇÃO PARA A OTIMIZAÇÃO DE TRANSPORTE. Journal of Open Research, 5(1). Retrieved from https://stellata.com.br/journals/jor/article/view/44

Issue

Vol. 5 No. 1 (2024): JOURNAL OF OPEN RESEARCH

Section

Articles