C. H. Robinson Uses Heuristics to Solve Rich Vehicle Routing Problems

TL;DR

This paper presents a set partitioning framework with heuristic route generation algorithms designed to efficiently solve complex, real-world vehicle routing problems faced by C.H. Robinson, outperforming existing methods on benchmark instances.

Contribution

The paper introduces a versatile set partitioning approach with heuristics tailored for rich vehicle routing problems, successfully applied within a commercial logistics platform.

Findings

Outperformed existing technologies on 10 benchmark instances

Embedded into C.H. Robinson's transportation planning platform

Effective across various problem variants with complex constraints

Abstract

We consider a wide family of vehicle routing problem variants with many complex and practical constraints, known as rich vehicle routing problems, which are faced on a daily basis by C.H. Robinson (CHR). Since CHR has many customers, each with distinct requirements, various routing problems with different objectives and constraints should be solved. We propose a set partitioning framework with a number of route generation algorithms, which have shown to be effective in solving a variety of different problems. The proposed algorithms have outperformed the existing technologies at CHR on 10 benchmark instances and since, have been embedded into the company's transportation planning and execution technology platform.