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Authors: Miguel Milheiro Ferreira 1 ; 2 ; Henrique Lopes Cardoso 1 ; 2 ; Luís Paulo Reis 1 ; 2 ; Telmo Barros 1 ; 2 and João Pedro Machado 3

Affiliations: 1 Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal ; 2 Laboratório de Inteligência Artificial e Ciência de Computadores (LIACC), Portugal ; 3 Autoridade de Segurança Alimentar e Económica (ASAE), Rua Rodrigo da Fonseca, 73, 1269-274 Lisboa, Portugal

Keyword(s): Vehicle Routing, Disruption Management, Real-time Scheduling, Routes Rescheduling, Hill-climbing, Simulated Annealing, Tabu-search, Large Neighbourhood Search.

Abstract: The emergence of technologies capable of producing real-time data opened new horizons to planning and optimising vehicle routes. Dynamic vehicle routing problems (DVRPs) use real-time information to dynamically calculate the most optimised set of routes. The typical approach is to initially calculate the vehicle routes and dynamically revise them in real-time. This work uses the case study of ASAE, a Portuguese administrative authority specialising in food safety and economic surveillance. The dynamic properties of ASAE’s operational environment are studied, and a solution is proposed to review and efficiently modify the precalculated plan. We propose a weighted utility function based on three aspects: the summed utility of the inspections, the similarity between solutions, and the arrival time. A Disruption Generator generates disruptions on the inspection routes: travel and inspection times, vehicle and inspection breakdowns, utility changes, and unexpected or emerging inspections. We compare the performance of four meta-heuristics: Hill-Climbing (HC), Simulated Annealing (SA), Tabu-Search (TS) and Large neighbourhood Search (LNS). The HC algorithm has the fastest convergence, while SA takes longer to solve the test instances. LNS was the method with higher solution quality, while HC provided solutions with lower utility. (More)


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Paper citation in several formats:
Ferreira, M.; Cardoso, H.; Reis, L.; Barros, T. and Machado, J. (2022). Disruption Management of ASAE’s Inspection Routes. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 810-817. DOI: 10.5220/0010914000003116

author={Miguel Milheiro Ferreira. and Henrique Lopes Cardoso. and Luís Paulo Reis. and Telmo Barros. and João Pedro Machado.},
title={Disruption Management of ASAE’s Inspection Routes},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},


JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Disruption Management of ASAE’s Inspection Routes
SN - 978-989-758-547-0
IS - 2184-433X
AU - Ferreira, M.
AU - Cardoso, H.
AU - Reis, L.
AU - Barros, T.
AU - Machado, J.
PY - 2022
SP - 810
EP - 817
DO - 10.5220/0010914000003116
PB - SciTePress