Cost-Optimal Egg Procurement Planning via MILP: A Smart System for Demand Satisfaction Under Fuzzy Constraints

Abstract

This study optimizes turkey egg supply planning for a meat production company. The primary objective is to determine optimal weekly procurement quantities that minimize costs while effectively meeting production demands and hatchery schedules. Both domestic and international suppliers with varying capacities transportation and costs are handled. The originality of this study lies in integrating detailed real-world constraints—supplier variability international logistics complexities regulatory requirements breed-specific considerations and hatchery limitations—through an inclusive Mixed-Integer Linear Programming (MILP) model. For balanced resource allocation suppliers breed types and penalty costs applied to excess supply and unmet demand are assigned. Procurement decisions all together optimize transportation customs clearance ordering costs and supplier selection. Computational experiments using real-life data demonstrate improved procurement efficiency reduced waste due to surplus and perishability and enhanced operational stability. This approach prevents bottlenecks ensuring cost-effective resource utilization. Results validate the model’s effectiveness in streamlining procurement strategies for perishable goods supply chains. © 2025 Elsevier B.V. All rights reserved.