A Multiobjective Mathematical Model of Reverse Logistics for Inventory Management with Environmental Impacts: An Application in Industry

TL;DR

This paper develops multiobjective mathematical models for reverse logistics inventory management, considering environmental impacts, and provides solution algorithms validated through numerical experiments, addressing sustainability in industrial processes.

Contribution

It introduces new models that account for different demands for new and remanufactured items and incorporates environmental objectives, extending prior models.

Findings

Validated models through numerical experiments

Developed a three-objective model for environmental impact, cost, and service level

Provided algorithms to obtain Pareto optimal solutions

Abstract

We propose new mathematical models of inventory management in a reverse logistics system. The proposed models extend the model introduced by Nahmias and Rivera with the assumption that the demand for newly produced and repaired (remanufacturing) items are not the same. We derive two mathematical models and formulate unconstrained and constrained optimization problems to optimize the holding cost. We also introduce the solution procedures of the proposed problems. The exactness of the proposed solutions has been tested by numerical experiments. Nowadays, it is an essential commitment for industries to reduce greenhouse gas (GHG) emissions as well as energy consumption during the production and remanufacturing processes. This paper also extends along this line of research, and therewith develops a three-objective mathematical model and provides an algorithm to obtain the Pareto solution.