In today’s intensely competitive industrial landscape, firms are under constant pressure to innovate and minimize operational costs. Traditional approaches that focus separately on production, inventory, procurement, and distribution are proving insufficient. This paper addresses the growing need for an integrated supply chain framework, particularly for perishable products, where shelf life constraints impose critical planning challenges.

We propose a novel integrated model that simultaneously optimizes the procurement of perishable raw materials, production scheduling, and distribution planning to ensure timely delivery before product spoilage. The model accounts for the cumulative time from raw material storage through production and multi-echelon distribution, ensuring it remains within the product’s lifetime. A Mixed-Integer Linear Programming  formulation is developed to capture these complex interdependencies, and alternative metaheuristic approaches are explored to address computational scalability for larger instances.

The results from computational experiments demonstrate the effectiveness and efficiency of the proposed approach, revealing substantial cost savings and improved service levels compared to disjointed strategies. Our model not only minimizes wastage and cost but also enhances customer satisfaction—offering significant promise for industries dealing with short-life products. This research contributes a novel optimization framework with practical relevance for perishables-based supply chains.