@article{ref1,
title="Conscious exploration of alpha-cuts in the parametric solution of the school bus routing problem with fuzzy walking distance",
journal="Computational intelligence and neuroscience",
year="2022",
author="Sánchez-Ansola, Eduardo and Pérez-Pérez, Ana C. and Rosete, Alejandro and Torres-Pérez, Isis and Rojas, Omar and Sosa-Gómez, Guillermo",
volume="2022",
number="",
pages="e4821927-e4821927",
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. <br><br>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.<p /> <p>Language: en</p>",
language="en",
issn="1687-5265",
doi="10.1155/2022/4821927",
url="http://dx.doi.org/10.1155/2022/4821927"
}