2014
DOI: 10.1016/j.energy.2014.08.048
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A stochastic programming approach towards optimization of biofuel supply chain

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Cited by 98 publications
(30 citation statements)
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“…Effective design, planning and management of forest biomass energy plants play a critical role in reducing the energy generation cost and making it a viable energy source (Shabani et al 2014). Recent advances in computational tools have made possible to build mathematical models for analysis and optimisation of complex supply systems (Azadeh et al 2014). Many approaches have been used to simulate and optimise specific biomass supply chains, to get a better understanding of the cost reductions that could result from the implementation of more efficient logistics operations while ensuring a reliable and sustainable supply of forest fuel (Rentizelas et al 2009).…”
mentioning
confidence: 99%
“…Effective design, planning and management of forest biomass energy plants play a critical role in reducing the energy generation cost and making it a viable energy source (Shabani et al 2014). Recent advances in computational tools have made possible to build mathematical models for analysis and optimisation of complex supply systems (Azadeh et al 2014). Many approaches have been used to simulate and optimise specific biomass supply chains, to get a better understanding of the cost reductions that could result from the implementation of more efficient logistics operations while ensuring a reliable and sustainable supply of forest fuel (Rentizelas et al 2009).…”
mentioning
confidence: 99%
“…Constraint set (26) indicates that if final market m is selected (i.e., E m ¼ 1), the sum of the flow of biodiesel shipped to that market should be between the maximum and minimum demand. Constrain set (27) ensures that the total biodiesel production in all production facilities is not less than the target demand in the entire nation.…”
Section: Demand Constraintsmentioning
confidence: 99%
“…This equation indicates that the total amount of liquid containing cellulose extracted under pretreatment processes should equal the amount of feedstock transported to the plant, multiplied by the performance efficiency associated with different pretreatment technologies ( η E,b−c,τ E ) [36].…”
Section: Pretreatment Levelmentioning
confidence: 99%
“…Equation (2) is a constraint which shows that the total amount of bioethanol produced from technology τ C equals the amount of liquid delivered to the refinery from the pretreatment step, multiplied by the associated energy conversion efficiencies of the fermentation and dehydration units, η C Ferm ,c−be,τ C and η C Dehyd ,c−be,τ C [36].…”
Section: Bioethanol Production Levelmentioning
confidence: 99%
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