A fuzzy multiobjective linear programming model for design and management of anaerobic digestion based bioenergy supply chains

The purpose of this study is to develop a decision support system (DSS) for design and management of anaerobic digestion based biomass to energy supply chains in a cost effective and environment friendly manner by tackling inherent uncertainties. To this aim, a fuzzy multiobjective mixed integer lin...

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Vydáno v:Energy (Oxford) Ročník 74; s. 928 - 940
Hlavní autoři: Yılmaz Balaman, Şebnem, Selim, Hasan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Kidlington Elsevier Ltd 01.09.2014
Elsevier
Témata:
Anaerobic digestion
Applied sciences
bioenergy
Bioenergy supply chain design
Biogas
Biomass
cost effectiveness
Decision support systems
Design engineering
Energy
Exact sciences and technology
Fuzzy
Fuzzy goal programming
Fuzzy logic
Fuzzy set theory
Linear programming
Management
Mixed integer linear programming
Natural energy
supply chain
uncertainty
Fuzzy goal programming
Bioenergy supply chain design
Biogas
Mixed integer linear programming
Anaerobic digestion
Supply
Linear programming
Biomass
Power production
Linear model
ISSN:0360-5442
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Popis
Shrnutí:The purpose of this study is to develop a decision support system (DSS) for design and management of anaerobic digestion based biomass to energy supply chains in a cost effective and environment friendly manner by tackling inherent uncertainties. To this aim, a fuzzy multiobjective mixed integer linear programming (MILP) model is constructed. To explore the viability of the proposed model, computational experiments are performed on a real world problem. The results reveal that the proposed model can effectively be used in practice. •An MILP based DSS is developed for design and management of bioenergy supply chains.•The proposed DSS integrates multiobjective decision making and fuzzy modeling.•Specific characteristics of anaerobic digestion systems are represented by the model.•The model is solved by using different FGP approaches.•Computational results expose that the model can effectively be used in practice.
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ISSN:0360-5442
DOI:10.1016/j.energy.2014.07.073