PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 8, 20260 citationsOpen Access

A Matheuristic for the Distance Constrained Inventory Routing Problem

View Full Paper
VVVíctor Manuel Valenzuela-AlcarazEREfraín Ruiz-y-RuizARAlma Danisa Romero-Ocaño

Key Points

  • The research aims to enhance the resolution efficiency of the Distance Constrained Inventory Routing Problem (DCIRP) while considering specific constraints.
  • Proposed a Mixed Integer Linear Programming (MILP) formulation for DCIRP.
  • Developed a matheuristic using an inventory-first, route-second (IFRS) approach.
  • Utilized a local search procedure to refine solutions.
  • The matheuristic produced high-quality solutions effectively.
  • Demonstrated reasonable computational effort for solution generation.
  • Improved sustainability of operations through optimized routing and inventory management.

Abstract

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 variant of the Inventory Routing Problem (IRP), and an NP-hard combinatorial optimization problem. 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 matheuristic that uses an inventory-first, route-second (IFRS) approach, including a minimum route cost approximation and a local search procedure. The results show that the proposed matheuristic produces high-quality solutions with a reasonable computational effort.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Valenzuela-Alcaraz et al. (2026) studied this question.

synapsesocial.com/papers/69ada9bbbc08abd80d5bcba9https://doi.org/10.3390/math14050907
Ask AI
Helpful
Bookmark
Share
View Full Paper