Crowdsourced logistics: The pickup and delivery problem with transshipments and occasional drivers

Abstract

This article considers a setting in which a courier, express, and parcel service provider operates a fleet of vehicles with regular drivers (RDs) to ship parcels from pickup to delivery points. Additionally, the company uses a platform where occasional drivers (ODs) offer their willingness to take on requests that are on or near the route they had originally planned. There exist transshipment points (TPs) to better integrate these ODs. ODs or RDs may transfer load at these predetermined TPs. The problem is modeled as a mixed-integer programming model and called pickup and delivery problem with transshipments and occasional drivers (PDPTOD). We develop a solution approach based on an adaptive large neighborhood search. The article provides insights on how the number and location of TPs impact the cost advantages achieved by integrating ODs. It also shows that the cost savings are highly sensitive to the assumed flexibility and compensation scheme.

Directions for future research on urban mobility and city logistics

“…The vehicle routes are periodic and static, while the parcel routes are determined dynamically based on capacity consideration and the location of the vehicles when a parcel arrives. Another approach is to opportunistically outsource the transportation tasks between SPs in the network to drivers who follow their regular trips and are ready to collect parcels and drop them somewhere later on their planned route in exchange for a monetary reward [78, 93].…”

Meal delivery routing optimization with order allocation strategy based on transfer stations for instant logistics services

“…To increase the flexibility of delivery systems, some studies focus on the PDP with transshipments. Voigt et al [21] propose the PDP considering the possibility of transshipments between drivers for crowdsourced logistics in last-mile delivery, and develop a heuristic solution approach based on ALNS to solve it. Wolfinger [22] addresses a PDPTW with split loads and transshipments and constructs an arc-based mixed integer model, which is solved by the large neighbourhood search (LNS) algorithm.…”

An Auction-Based Multiagent Simulation for the Matching Problem in Dynamic Vehicle Routing Problem with Occasional Drivers

“…Crowdsourced delivery applies the concept of crowdsourcing to logistics [6]. According to the structure proposed by Nourinejad and Roorda [7], there are two types of methods for dealing with the evaluation of crowdsourced delivery in last-mile logistics: centralized and decentralized.…”

“…us, compensation schemes were included and discussed in the context of the PDPOD by Dahle et al [16]. In the same research stream as the PDPOD, the impact of allowing for task transfer between ODs was investigated by Voigt and Kuhn [6]. eir numerical results showed that the introduction of trans-shipment points increased the utilization of ODs and significantly reduced total cost.…”

“…Update the list of online orders and occasional drivers (5) Update current bid list for each online order (6) if t � scheduled auction match time then (7) Run auction-based matching procedure (8) end if (9) if t � scheduled regular vehicle departure time then (10) Run regular vehicle routing procedure (11) end if (12) t � t + Δ t (13) end while ALGORITHM 1: Whole simulation procedure. capacity, frequency of bidding, and compensation threshold.…”