Genetic Algorithm Applied to Problem Solving p-hub Multiple Unallocated Center

  • Jardell da Silva CEFET-MG
  • Flavio Martins CEFET-MG
  • Maria Silva CEFET-MG
  • Sérgio de Souza CEFET-MG

Abstract


This work addresses a variant of the p-hub Center (pHCP) problem, named the Unassigned Multi-Allocation Center p-Hub Problem (UMApHCP). The problem is to define p hubs in a complete graph so that the maximum transport cost of the graph is minimized. A Hybrid Genetic Algorithm (GA) is used to solve the problem addressed, with the initial population generated by the GRASP metaheuristic construction phase. In addition to each hub configuration generated by the GA, a polynomial-time algorithm is applied to determine the optimal allocation of the nodes of the graph. To evaluate the GA, 2 sets of instances with up to 300 nodes and 40 hubs available in the literature were used. Computational tests are performed in order to prove the efficiency of the proposal.

Keywords: Optimization, UMApHCP, Metaheurístics, Genetic Algorithm

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Published
2019-10-15
SILVA, Jardell da; MARTINS, Flavio; SILVA, Maria; SOUZA, Sérgio de. Genetic Algorithm Applied to Problem Solving p-hub Multiple Unallocated Center. In: NATIONAL MEETING ON ARTIFICIAL AND COMPUTATIONAL INTELLIGENCE (ENIAC), 16. , 2019, Salvador. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 856-867. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2019.9340.