RT Journal Article
T1 Variable neighborhood search to solve the generalized orienteering problem
A1 Urrutia Zambrana, Adolfo
A1 Tirado Domínguez, Gregorio
A1 Mateos, Alfonso
AB This paper presents a variable neighborhood search (VNS) algorithm to solve the extension of the orienteering problem known as the generalized orienteering problem (GOP). Our algorithm aims to use a reduced number of neighborhoods without compromising the quality of the results. This reduced number of neighborhoods, together with the precalculation of scores associated with points of interest, allows us, in most cases, to outperformall previous metaheuristics proposed for this problem. This is the first time a VNS is being applied to theGOP, and it provides promising computational results. In particular, in the case studies considered in the paper, we were able to find 35 new best solutions, all of which were found using a shorter computational time. Furthermore, the information regarding other best-known solutions provided in the literature has also been improved, with corrections to some previously published errors regarding scores and distances. In addition, the benchmark has been extended with the incorporation of new case studies based on real data from three of the most popular tourist cities in Spain.
PB Wiley
SN 0969-6016
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/94963
UL https://hdl.handle.net/20.500.14352/94963
LA eng
NO Urrutia‐Zambrana, Adolfo, Gregorio Tirado, y Alfonso Mateos. «Variable Neighborhood Search to Solve the Generalized Orienteering Problem». International Transactions in Operational Research 28, n.o 1 (enero de 2021): 142-67. https://doi.org/10.1111/itor.12800.
NO Ministerio de Economía y Competitividad (España)
NO European Commission
NO Comunidad de Madrid
DS Docta Complutense
RD 17 dic 2025