Two-phase matheuristic for assignment and truck loading problems

Abstract

We introduce a novel two-phase matheuristic for assignment and truck loading. The scope of our approach involves scenarios with an extensive amount of items requiring assignment to a heterogeneous fleet of trucks and subsequent transportation. A distinguishing feature of our matheuristic lies in the fact that the complex underlying problem is divided into subproblems which later are merged into a global solution. The proposed matheuristic tackles the assignment problem in its first phase, followed by a complex truck loading algorithm to validate the assignment solution in the second phase. This enables the identification of optimal solutions and adaptability to diverse use cases. This approach is motivated by the ROADEF/EURO challenge 2022 and is awarded with the scientific prize of the challenge. We demonstrate superior performance on selected instances, showcasing the potential for significant cost reduction in Renault’s supply chains.