A Fuzzy Optimization Approach to Integration of Physical and Financial Flows in a Global Supply Chain Under Exchange Rate Uncertainty

In recent years, increasing costs and organization concerns regarding the funding and allocation of financial resources have resulted in a great attention to financial flow and its effects on planning decisions through supply chain network. This study aims at developing a mathematical model that is able to integrate the financial and physical flows in the global supply chain planning problem. To evaluate the financial performance of the supply chain, economic value added index is used. The proposed model utilizes a new risk measure, i.e., fuzzy CVaR to cope with the uncertainty of exchange rate as an important factor in global supply chains. To demonstrate the efficiency of the proposed model, a test problem from the recent literature is used. The analysis of the results obtained from the developed fuzzy mathematical model shows an average 5% increase in profit and 10% reduction in the semi-variance measure compared to previously developed models.