Abstract
According to the high sugar and oil content of algae, the algal biofuel have been taken into consideration in recent years. This paper develops a multi-objective mixed integer quadratic programming (MMIQP) model to optimize the design and planning of an algae-based biofuel supply chain network under environmental and economic objectives. The goals of this paper are set to maximize the total profit and carbon dioxide absorption of the supply chain. The proposed mathematical model considers the deterioration issue in the inventory and during the transportation, in a multi-period time horizon. Since the alternative fuel price is not certain in the real world, a two-stage stochastic programming is utilized to address this uncertainty. Moreover, data envelopment analysis (DEA) approach is proposed to rank the candidate cities based on efficiency for microalgal harvesting. The applicability and efficiency of the proposed model are finally demonstrated through a real case study in Iran.
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