Sustainable solutions analysis of a bi-objective green inventory routing problem with heterogeneous fleet and different types of fuels

Author(s)

Mundim, Arianne A. S. ; Santos, Maristela O. ; Morabito, Reinaldo

• Document type: Journal article
• Source: RAIRO-OPERATIONS RESEARCH; v. 59, n. 1, p. 30-pg., 2025-02-14.

Abstract

One of the main agents responsible for global warming is greenhouse gases, especially carbon dioxide (CO2) associated with fuel combustion. Most works in the literature address logistics transportation from an economic perspective, giving little attention to the existing trade-off with sustainability. In this work, we develop a bi-objective approach to the inventory routing problem with heterogeneous fleet, where we minimize costs while simultaneously reducing CO2 emissions. First, we present an explicit vehicular equation developed to calculate CO2 emissions for different types of vehicles and fuels. We demonstrate that this equation is statistically precise by conducting a study with a database in which machine learning techniques were applied to assess the predictive accuracy of CO2 emissions. The comparison between the explicit equation and machine learning models proves its efficacy as a suitable approximation for practical applications. Then, we propose an augmented epsilon-constrained method to find the efficient Pareto frontier using a branch-and-cut method. Computational experiments were conducted on 285 instances, of which 125 were adapted from the literature, solving the augmented epsilon-constrained optimally. Result analysis indicates the ability of the approach to trade off between economy and sustainability, where, on average, lexicographic solutions show a 58% reduction in emissions and a 36% increase in costs. We conclude with a managerial analysis providing insights into the proposed approach, highlighting the advantages of using different vehicles and fuels. (AU)

• FAPESP's process: 16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings
• Grantee: Reinaldo Morabito Neto
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: Francisco Louzada Neto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC