Approaching the Pareto Front in a Biobjective Bus Route Design Problem Dealing with Routing Cost and Individuals’ Walking Distance by Using a Novel Evolutionary Algorithm

Calvete, Herminia I. (Universidad de Zaragoza) ; Galé, Carmen (Universidad de Zaragoza) ; Iranzo, José A. (Universidad de Zaragoza)

Resumen: This paper addresses a biobjective bus routing problem that pays attention to both the routing cost and the total distance walked by the individuals to reach their assigned pickup point. These two objectives are conflicting. Generally, the less the individuals walk, the more the number of visited pickup points and so the more the routing cost. In addition, the problem deals with finding the set of pickup points visited among the set of potential locations, identifying the set of individuals assigned to each visited pickup point, and designing the bus routes. Taking into account the highly combinatorial nature of the problem, an evolutionary algorithm is proposed to approach the associated Pareto front. Its main novelties are twofold. The first is the way in which the chromosomes are encoded since they only provide information about the number of routes and the visited pickup points. The second novelty lies in the procedure to construct a feasible solution from the chromosome, which involves a heuristic and several local search procedures to improve both objective functions. Computational experiments are carried out to check the performance of the algorithm in terms of the quality of the Pareto front yielded.

Idioma: Inglés

DOI: 10.3390/math10091390

Año: 2022

Publicado en: Mathematics 10, 9 (2022), 1390 [17 pp.]
ISSN: 2227-7390

Factor impacto JCR: 2.4 (2022)

Categ. JCR: MATHEMATICS rank: 23 / 329 = 0.07 (2022) - Q1 - T1

Factor impacto CITESCORE: 3.5 - Engineering (Q2) - Mathematics (Q1) - Computer Science (Q2)

Factor impacto SCIMAGO: 0.446 - Computer Science (miscellaneous) (Q2) - Mathematics (miscellaneous) (Q2) - Engineering (miscellaneous) (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E41-20R
Financiación: info:eu-repo/grantAgreement/ES/MCIU/PID2019-104263RB-C43

Tipo y forma: Article (Published version)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)