Conscious Exploration of Alpha-Cuts in the Parametric Solution of the School Bus Routing Problem with Fuzzy Walking Distance

Eduardo Sánchez-Ansola; Ana C. Pérez-Pérez; Alejandro Rosete; Isis Torres-Pérez; Rojas, Omar; Sosa-Gómez, Guillermo

doi:10.1155/2022/4821927

Conscious Exploration of Alpha-Cuts in the Parametric Solution of the School Bus Routing Problem with Fuzzy Walking Distance

Journal

Computational Intelligence and Neuroscience

ISSN

1687-5273

1687-5265

Date Issued

2022

Author(s)

Eduardo Sánchez-Ansola

Ana C. Pérez-Pérez

Alejandro Rosete

Isis Torres-Pérez

Type

Resource Types::text::journal::journal article

DOI

10.1155/2022/4821927

URL

https://scripta.up.edu.mx/handle/20.500.12552/4229

Abstract

Combinatorial optimization problems allow for modeling multiple situations in which proper allocation of resources is needed. For some real-world problems, the use of fuzzy elements in the models allows for incorporating certain levels of uncertainty to better approximate such real-world situations. One way to solve combinatorial optimization problems with fuzzy elements is the parametric approach, where it is necessary to define how to explore different relaxation levels using alpha-cuts. Researchers tend to select such alpha-cuts uniformly. The current investigation proposes a novel strategy for selecting alpha-cuts in the School Bus Routing Problem with fuzzy students’ maximum walking distance. This proposal bases its foundations on the number of student-bus stop pairs available according to the different levels of relaxations allowed. Results demonstrate how the proposed strategy gives attractive solutions with more diverse trade-offs, contrasted with other methods in the literature. Furthermore, it decreases the computational cost for those instances where the maximum relaxation does not provide new pairs of students-bus stops.