Modeling and optimization approaches for biomass to energy supply chain network design of increasing scope and sophistication have been devised recently. However, network design models for the bioenergy supply chains including anaerobic digestion facilities have not been dealt with in the previous research although it is one of the most efficient and environment friendly energy production systems. Also, the vast majority of the related studies consider only energy crops as biomass resource. As improper disposal or storage
of organic wastes causes pollution in underground and surface waters and environmental problems that threat human health, constructing waste biomass to energy conversion plants is vital in decreasing such problems besides gaining economical benefits.
Since integrating FST with multiobjective optimization tech- niques provides the real system to be modeled more realistically and closer to the decision maker's needs, fuzzy modeling ap- proaches become prominent in decision making for preference modeling and multi criteria/objective evaluation. We propound that fuzzy multiobjective decision making (FMODM) approach can effectively be used in design and management of bioenergy supply chains. Considering these facts and the gaps in the literature, this study aims to develop a fuzzy multiobjective MILP based DSS (de- cision support system) for design and management of biomass to energy supply chains that include anaerobic digestion facilities.
The proposed model includes environmental and economic objectives and it is structured as multiperiod to incorporate varia- tion and seasonality in feedstock supply and cost parameters. In addition, multiple types of biomass and products are incorporated in the model. To provide the decision makers for a more confident solution set for policy decision making, the model is solved by using different FGP (fuzzy goal programming) approaches and the results are evaluated. To explore the viability of the proposed DSS, appli- cations of the model with different FGP approaches are performed on a real world problem.