Simulation-Driven Cost Evaluation of Food Product Returns in Reverse Logistic Supply Chains

Abstract

Food supply chains are experiencing a sustained increase in return volumes due to product expiration, handling and transportation damage, order fulfillment errors, demand variability, and commercial policies. These returns trigger reverse logistics processes that incorporate additional transportation, inspection, sorting, and disposal activities, generating significant costs that are often neither systematically quantified nor explicitly integrated into logistics planning and strategic decision-making. The objective of this study is to determine the proportion represented by transportation costs associated with food product returns in Costa Rica relative to total transportation costs, considering both deliveries and returns to and from the distribution centers of five modern retail supermarket chains. To achieve this objective, a discrete-event simulation model was developed to integrate forward and reverse distribution processes between the manufacturer and the analyzed chains, incorporating operational variability and logistical constraints. The results indicate that return-related costs exhibit stable and predictable behavior, with an estimated average annual cost of $14,486.06, equivalent to 29.24% of total transportation costs. The low relative variability (coefficient of variation of 4.44%) and the approximately symmetric distribution suggest a mature and well-controlled logistics system. These findings highlight the need to explicitly incorporate reverse logistics into the evaluation and optimization of food distribution systems in order to enhance economic efficiency and operational sustainability.