An integrated model for the optimisation of a two-echelon supply network

Purpose: The purpose of this paper is to develop a mixed integer formulation that extends the previous production-distribution models by the integration of Aggregate Production Plan and Distribution Plan. Design/methodology/approach: This paper, firstly, presents a comprehensive review and analysis on the proposed production-distribution models and would develop a summary table to describe the main characteristics of the selected models outlining the level of complexity considered at each study. Based on the integration of Aggregate Production Plan and Transportation/Distribution Plan, over the second stage, the paper will develop a mixed integer formulation for a two-echelon supply network. The model incorporates multi-time periods, multi-products, multi-plants, multi-warehouses as well as multi-end users, and considers the real-world variables and constraints. Finally, the developed model will be analyzed in case of a realistic scenario-based production-distribution problem. Findings: This paper developed a mixed integer formulation for the optimization of a two-echelon SN. Considering detailed production cost elements and a realistic range of variables and constraints in the proposed case study indicate the effectiveness of the developed model in the real-world applications. Practical implications: The increasing interest in evaluating the performance of SNs over the last years indicates the need for the development of complex optimization models able to answer unsolved questions in the production-distribution network. Originality/value: Implementation of a supply-chain (SC) system has crucial impacts on a companys financial performance. Overall performance of a Supply Network (SN) is influenced significantly by the decisions taken in its production-distribution plan integrating the decisions in production, transport and warehousing as well as inventory management. Thus, one key issue in the performance evaluation of SNs is the modeling and optimization of production-distribution plan considering its actual complexity