A Bi-objective Robust Optimization Model for an Integrated Production-distribution Problem of Perishable Goods with Demand Improvement Strategies: A Case Study

This paper develops a bi-objective optimization model for the integrated production-distribution planning of perishable goods under uncertainty. The first objective seeks to maximize the profit in a specific supply chain with three levels: plants, distribution centers, and in the last level, customers. Since transportation is one of the major pollution sources in a distribution problem, the second objective is to minimize their emission. In the considered problem, the decisions of production, location, inventory, and transportation are made in an integrated structure. In developing the demand function, the effect of the product freshness and the price is formulated. Besides, to encourage customers, three strategies, including perished product return, discount, and credit policies, are proposed. Also, robust optimization is utilized to cope with the operational uncertainty of some cost parameters. To prove the applicability of this research and the feasibility of the environmental aspect, a case study is conducted. Finally, the numerical computations on the case study provide a trade-off between the environmental and economic goals and indicate a 37.5 percent increase in the profit using the developed model.

Automated summary

This study developed a bi-objective optimization model for integrated production-distribution planning of perishable goods under uncertainty, aiming to maximize profit while minimizing emissions. Through an integrated consideration of production, location, inventory, and transportation decisions, the model achieved a 37.5% increase in profit by balancing environmental and economic goals, as demonstrated in a case study.