Individually Rational Collaborative Vehicle Routing through Give-And-Take Exchanges

TL;DR

This paper presents a multi-agent algorithm for collaborative vehicle routing that enables logistics companies to exchange orders through Give-and-Take exchanges, reducing travel distances and ensuring individual rationality for sustainable cooperation.

Contribution

It introduces a novel multi-agent approach to CVRP that guarantees individual rationality and faster convergence, facilitating sustainable cooperation among competing logistics companies.

Findings

Reduces total travel distance in logistics networks

Ensures individual rationality for all participating agents

Rapidly identifies multiple optimal routing solutions

Abstract

In this paper, we are concerned with the automated exchange of orders between logistics companies in a marketplace platform to optimize total revenues. We introduce a novel multi-agent approach to this problem, focusing on the Collaborative Vehicle Routing Problem (CVRP) through the lens of individual rationality. Our proposed algorithm applies the principles of Vehicle Routing Problem (VRP) to pairs of vehicles from different logistics companies, optimizing the overall routes while considering standard VRP constraints plus individual rationality constraints. By facilitating cooperation among competing logistics agents through a Give-and-Take approach, we show that it is possible to reduce travel distance and increase operational efficiency system-wide. More importantly, our approach ensures individual rationality and faster convergence, which are important properties of ensuring the long-term sustainability of the marketplace platform. We demonstrate the efficacy of our approach through extensive experiments using real-world test data from major logistics companies. The results reveal our algorithm's ability to rapidly identify numerous optimal solutions, underscoring its practical applicability and potential to transform the logistics industry.