Multi-Location Assortment Optimization with Drone and Human Courier Joint Delivery

This paper studies the constrained multi-location assortment optimization problem under joint delivery by drone and human courier. To maximize the revenue of the retailer, product assortment and last-mile delivery methods are configured simultaneously. To handle the joint delivery problem with produ...

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Bibliographic Details
Main Authors: Pei, Z. (Author), Wu, M. (Author)
Format: Article
Language:English
Published: MDPI 2023
Subjects:
Online Access:View Fulltext in Publisher
View in Scopus
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020 |a 20763417 (ISSN) 
245 1 0 |a Multi-Location Assortment Optimization with Drone and Human Courier Joint Delivery 
260 0 |b MDPI  |c 2023 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/app13095441 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159291157&doi=10.3390%2fapp13095441&partnerID=40&md5=7da3e81ff95375deadd2ea4722d910d0 
520 3 |a This paper studies the constrained multi-location assortment optimization problem under joint delivery by drone and human courier. To maximize the revenue of the retailer, product assortment and last-mile delivery methods are configured simultaneously. To handle the joint delivery problem with product assortment, a mixed multinomial logit model is established to depict the customer purchase behavior. We also take into account the load capacity of drones and the delivery distance limit of drones and human couriers. To the best of our knowledge, the present paper is the first to study the assortment optimization problem considering joint delivery by drone and human courier. The problem is first formulated as a mixed-integer linear programming (MILP) model, which is then transformed into a conic quadratic mixed-integer model with McCormick inequalities (Conic + MC). In the numerical study, it is demonstrated that Conic + MC outperforms MILP as Conic + MC finds the optimal solution within 300 s, while MILP needs more than 600 s. Furthermore, several management insights are revealed for retailers regarding assortment planning when facing different kinds of product revenue structures, and advice is provided for online ordering platforms in terms of setting delivery limits. © 2023 by the authors. 
650 0 4 |a assortment 
650 0 4 |a conic integer optimization 
650 0 4 |a drone 
650 0 4 |a multi-location 
700 1 0 |a Pei, Z.  |e author 
700 1 0 |a Wu, M.  |e author 
773 |t Applied Sciences (Switzerland)