Journées de l'optimisation 2022
HEC Montréal, Québec, Canada, 16 — 18 mai 2022
WA11 - Vehicle routing and scheduling V
18 mai 2022 10h30 – 12h10
Salle: EY (bleu)
Présidée par Hani Zbib
10h30 - 10h55
A Continuum Approximation Approach to the Hub Location Problem in a Crowd-Shipping System
Last-mile delivery in the logistics chain contributes to emissions and increased congestion. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery, but relies heavily on the availability of occasional couriers. In this work, we propose a hub-based crowd-shipping system that aims to attract sufficient potential crowd-shippers to serve a large portion of the demand for small parcels. While small-scale versions of this problem have been recently addressed, a scaling to larger instances significantly complexifies the problem. A heuristic approach based on continuum approximation is designed to evaluate the quality of a potential set of hub locations. By combining an efficient and accurate approximation method with a large neighborhood search heuristic, we are able to efficiently find a good set of hub locations, even for large scale networks. Furthermore, on top of determining good hub locations, our methods allow to identify the expected number of delivered parcels in every region, which can be used to design a smart dynamic assignment strategy. A case study on the Washington DC network shows that hubs are built at locations that are both geographically central, but most importantly are popular origins for crowd-shippers. The optimal number of hubs is mainly dependent on the marginal number of parcels that can be served by crowd-shippers from a specific hub, relative to the costs involved in opening that hub. The performance of our algorithm is close to that of a simulation-optimization algorithm, yet being up to 25 times faster.
10h55 - 11h20
Vehicular Technologies in Recyclable Waste Collection: How Do They Affect Service?
Within the context of circular economies, recycling has gained a lot of traction, which consequently resulted in waste collection becoming more complex due to the many recycling-related technological features and configurations available on waste collection vehicles. These technological features can highly affect the efficiency of the recyclable waste collection service, mainly the collection time and the design of collection routes. We present a decision support tool for municipal entities responsible for recyclable waste collection from households to aid in their fleet mix decisions given the catalogue offering of a recycling trucks manufacturer. To that end, we analyse the catalogue offerings of several trucks manufacturers and identify the technological features of collection vehicles that affect the recyclable waste collection service, and show how these features and their different configurations can be modelled.