A Matheuristic for the Distance Constrained Inventory Routing Problem

This paper addresses the Distance-Constrained Inventory Routing Problem (DCIRP), a complex problem that combines inventory management and vehicle routing in a logistics context. The problem arises in the context of a specialty gas delivery company that maintains a specialty gas holding facility at each customer's site and uses several trucks to deliver specialty gas, with the additional constraint that drivers are limited to the number of kilometers they can drive each day. A Mixed Integer Linear Programming (MILP) formulation is proposed to model the DCIRP. The DCIRP is a combinatorial optimization problem of type NP-Hard. The main objective of this research is to improve the efficiency and effectiveness of DCIRP resolution, while accounting for vehicle capacity constraints, customer inventory levels, and delivery route distance constraints. By optimizing routes and inventory management, the company's operations become more sustainable. To solve the problem, three solution approaches are proposed. The first is an exact method based on the MILP formulation. The second is a mateheuristic using an inventory-first-route-second (IFRS) approach. The third solution algorithm also uses an IFRS approach, but includes a minimum route cost for each cost and a local search procedure. The results show that the third solution algorithm produces high-quality solutions with reasonable computational effort.