Paper Info
Title
Robust optimization for the hierarchical mixed capacitated general routing problem applied to winter road maintenance
Abstract
AbstractHighlights •We study the Mixed Capacitated General Routing Problem under a demand uncertainty.•The street hierarchy is modeled with time dependent cost.•We used robust optimisation to solve the problem.•We developed robust metaheuristic for winter road maintenance.•We used Monte Carlo simulation to study the robust approach on real-life case studies. AbstractThis paper studies the Mixed Capacitated General Routing Problem (MCGRP) under demand uncertainty and service hierarchy using a robust optimization approach. The problem is motivated by an industrial problem: the winter road salt spreading with street hierarchy and demand variation due to the weather or traffic conditions. The street hierarchy or the street priority is modeled with time-dependent cost. We present a robust counterpart formulation with graph transformation to node routing in order to optimize the worst-case realization of the demands from the uncertainty set. We use CPLEX to solve small instances and we developed a variant of the Slack Induction by String Removals metaheuristic for large-scale instances called the Robust SISRs. In the computational analysis we used a Monte carlo simulation to study the robust approach on real-life case studies.
Year
DOI
Venue
2021
10.1016/j.cie.2021.107396
Periodicals
Keywords
DocType
Volume
Robust optimization, General routing problem, Winter road maintenance, Time dependent cost, Arc routing problem
Journal
158
Issue
ISSN
Citations 
C
0360-8352
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Chahid Ahabchane100.34
André Langevin200.34
Martin Trépanier300.34