A Bi-Objective Mathematical Model for the Design of a Resilient Food Supply Chain Network: A Case Study of Korush Livestock an‎d Poultry Company

5/2/2026 12:00:00 AM

Designing food supply chain networks always faces the inherent challenge of balancing economic efficiency with resilience against disruptions. Characteristics such as perishability, time sensitivity, an‎d dependence on cold storage infrastructure make these chains highly vulnerable to deman‎d fluctuations, livestock diseases, an‎d logistical constraints. In such a context, focusing solely on cost minimization without considering resilience against disruptions not only reduces service levels but also causes the network to fail rapidly during crises. Therefore, providing a framework that can simultaneously address these two conflicting objectives is a strategic necessity. The aim of this research is to present a bi-objective mathematical model for designing a resilient supply chain network in the food industry. The proposed model is developed based on mixed-integer programming within a scenario-based two-stage stochastic programming framework. The main innovations of this study are summarized in four parts: (1) transforming the basic Shokrabi model into a genuine bi-objective model aimed at simultaneously minimizing economic cost an‎d internal shortage (as a resilience indicator) an‎d eliminating the shortage penalty term from the cost function to extract the true Pareto front; (2) designing a smart export policy as a fixed percentage applied only in normal scenarios, without a firm commitment under disruption conditions; (3) adding an internal service level constraint to guarantee a minimum response to domestic market deman‎d under normal scenarios; (4) modeling the ripple effect of disruptions with three intensity levels, three time periods, an‎d six geographical zones, resulting in the design of 54 scenarios. The model has been eva‎luated using the supply chain of Korosh Livestock an‎d Poultry Company, an‎d numerical data related to the livestock/red meat network have been prepared in a consistent data package (based on deman‎d aggregation by provincial population, per capita consumption, transportation costs, an‎d disruption parameters). The ε-constraint method was used to solve the model, an‎d the Pareto front was extracted with 15 points. The results show that increasing market coverage an‎d the export share significantly increases total cost, an‎d in critical combinations (25% market share with 20% exports), the model reaches the verge of infeasibility. Sensitivity analysis indicates that the service level parameter (α) is only effective in the presence of shortage, an‎d under high capacity pressure, increasing it merely raises costs without reducing shortage to zero. This model can serve as a decision-support tool for food industry managers in designing more resilient an‎d efficient networks under unstable conditions. Keywords: Resilient supply chain, Food industry, Network design, Risk management, Robust planning

زنجيره تامين تاب اور , صنعت غذا , طراحي شبكه

Resilient supply chain , Food industry , Network design

Amirmahdi Farsi

Dr.Ebrahim Teymori