Applications of Fuzzy Mathematical Programming Approaches in Supply Chain Planning Problems

Supply chain planning includes numerous decision problems over strategic (i.e. long-term), tactical (i.e. mid-term) and operational (i.e. short-term) planning horizons in a supply chain. As most of supply chain planning problems deal with decision making in real world while configuring future situations, relevant data should be predicted and described for multiple time periods in the future. Such prediction and description involve imprecision and vagueness due to errors and absence of sharp boundaries in the subjective data and/or insufficient or unreliable objective data. If the uncertainty in supply chain planning problems is to be neglected by the decision maker, the plausible performance of supply chain in future conditions will be in doubt. This is why considerable body of the recent literature account for uncertainty through applying different uncertainty programming approaches with respect to the nature of uncertainty. This chapter aims to provide useful and updated information about different sources and types of uncertainty in supply chain planning problems and the strategies used to confront with uncertainty in such problems. A hyper methodological framework is proposed to cope with uncertainty in supply chain planning problems. Also, among the different uncertainty programming approaches, various fuzzy mathematical programming methods extended in the recent literature are introduced and a number of them are elaborated. Finally, a useful case study is illustrated to present the practicality of fuzzy programming methods in the area of supply chain planning.