CORS / Optimization Days 

HEC Montréal, May 29-31, 2023


HEC Montreal, 29 — 31 May 2023

Schedule Authors My Schedule

ALME Advancement In Last-Mile Delivery: A Spotlight on Emerging Technologies

May 31, 2023 03:40 PM – 05:20 PM

Location: Société canadienne des postes (yellow)

Chaired by Bahar D Viniche

3 Presentations

  • 03:40 PM - 04:05 PM

    Integration of Smart Mobile Lockers and City Buses in E-commerce Deliveries: A Pricing Analysis

    • SI LIU, presenter,
    • Elkafi Hassini, McMaster University

    Parcel lockers offer an efficient and sustainable solution for last-mile delivery in the e-commerce sector. This study introduces an innovative concept called the Smart Mobile Locker in tandem with City Bus (SML-CB). By integrating with city buses, the SML-CB utilizes existing bus routes for mobility and bus stops as convenient delivery points. The implementation of SML-CB in various domains is still in its infancy. Our research is the first to evaluate financial feasibility and present a pricing analysis for the SML-CB system. We develop a model to estimate delivery costs through the SML-CB approach and compare these costs to those incurred using truck deliveries. The resulting savings are distributed among customers, the SML-CB platform, and couriers based on the beneficiary-pay principle, ensuring the SML-CB service is competitively priced.

  • 04:05 PM - 04:30 PM

    Design and Operation Optimization of a Food Delivery Service using a Multimodal Automated Fleet

    • Farzan Moosavi, presenter, Toronto Metropolitan University

    The last-mile delivery complexity has intensified due to ever-growing urbanization, rapid interest in e-commerce, and post-Covid effects on congested urban areas. Besides, it significantly impacts the level of service delivery in the local area. The newly emerging technologies, such as drones and sidewalk robots, can address this critical challenge. This paper presents an approach to multi-objective hybrid automated network design for the drone-and-robot last-mile delivery system. The main objective of this research is to design fleet, sizing, and allocation, to minimize the total waiting time of the customer to receive its package and the delivery cost of vehicles for the given number of orders and each vehicle's battery capacity and sizing capacity. Vehicle flight path regulations, including headway clearance and collision avoidance, are considered to capture the three-dimensional effect of drone trajectory. Mixed-integer linear programming is proposed to formulate the optimization problem along with the heuristic algorithm, such as benders decomposition, to find the optimal design of the delivery framework. By developing an optimization-based approach to satisfy demand fulfillment and operational constraints, we solve the routing and decision-making process for the effective and practical assignment of the vehicles. To ensure the network's sustainability, a detailed sensitivity analysis is conducted.

  • 04:30 PM - 04:55 PM

    Autonomous Vehicle Applications in Recipient-Dependent Deliveries

    • Bahar D Viniche, presenter, York University
    • Opher Baron, Rotman School of Management, University of Toronto
    • Oded Berman, Rotman School of Management, University of Toronto
    • Mehdi Nourinejad, York University

    Last-mile deliveries contribute to a drastic 28% of the total shipping cost. Recent technological advancements enable recipients to participate in these deliveries, relieving the cost of this final leg of the supply chain. We present models of recipient-dependent routing policies in last-mile logistics. The policies are based on scenarios where recipients pick up from (i) a central depot, (ii) a hub located by the logistics firm close to them (hybrid), (iii) a hub and deliver to nearby recipients (crowdsourcing). The policies are partially motivated by the future applications of autonomous vehicles in smart cities and their role in enabling recipient-dependent deliveries as they relinquish the need for drivers. We compare the policies with status quo truck delivery and investigate the potential cost savings. Our analysis shows a robust dominance space pattern against key operational parameters. In particular, (i) status quo truck routing is the currently preferred delivery policy, (ii) the dominance space of the hybrid and crowdsourcing policies is sandwiched by the dominance space of other policies, and (iii) recipient-dependent routing policies dominate the status quo truck policy as the number of recipients increases. We validate the insights from the stylized model with a case study of Walmart in Toronto.