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Enhancing Efficiency and Sustainability in Reverse Logistics Through Inventory Modelling for Cost Analysis and Environmental Impact Reduction
Abstract
As global environmental awareness grows, sustainable development is gaining momentum. A key strategy in achieving sustainability is the adoption of reverse logistics (RL), which manages the backward flow of materials from customers to manufacturers. This often occurs due to product damage, unmet expectations, or warranty returns. This study presents a comprehensive investigation using both mathematical analysis and computational tools. The mathematical model aims to minimize the planning horizon and maximize total profit, incorporating a non-constant return fraction and a carbon reduction function influenced by green technology investment. Computational analysis, performed using MATLAB, supports the theoretical framework. The main goal is to optimize profits in a reverse logistics system while addressing cost efficiency and environmental impact. The model focuses on reducing solid waste through repurposing materials for use in production and remanufacturing, and also determines the optimal conditions for manufacturers to achieve maximum profitability.
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