Modular Coordination of Vehicle Routing and Bin Packing Problems in Last Mile Logistics

<i>Background</i>: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. The paper describes a modular coordination of vehicle routing and bin packing problems that enables independent instances of the probl...

Full description

Saved in:
Bibliographic Details
Main Authors: Nikica Perić, Anđelko Kolak, Vinko Lešić
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Logistics
Subjects:
Online Access:https://www.mdpi.com/2305-6290/9/2/70
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:<i>Background</i>: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. The paper describes a modular coordination of vehicle routing and bin packing problems that enables independent instances of the problems to be joined together, with the aim that the vehicle routing solution satisfies all the constraints from real-world applications. <i>Methods</i>: The vehicle routing algorithm is based on an adaptive memory procedure that also incorporates a simple, one-dimensional bin packing problem. This preliminary packing solution is refined by a complex, three dimensional bin packing for each vehicle to identify the infeasible packages. The method iteratively adjusts virtual volumes until reaching near-optimal routes that respect bin-packing constraints. <i>Results</i>: The coordination enables independent applications of an adaptive memory procedure to vehicle routing and a genetic algorithm approach to bin packing while joining them in a computationally tractable way. Such a coordinated approach is applied to a frequently used public benchmark and proven to provide commensurate costs while significantly lowering algorithm complexity. <i>Conclusions</i>: The proposed method is further validated on a real industrial case study and provided additional savings of 14.48% in average daily distance traveled compared to the current industrial standard.
ISSN:2305-6290