A mathematical model for microalgae-based biobutanol supply chain network design under harvesting and drying uncertainties

Mahsa Arabi, Saeed Yaghoubi and Javad Tajik

Energy, 2019, vol. 179, issue C, 1004-1016

Abstract: Microalgae is one of the most promising feedstocks for biofuel production because it yields the high content of sugar and oil. In order to help to develop this nascent industry, this paper proposes a mixed integer linear programming (MILP) model for planning and designing a microalgae-based biobutanol supply chain network. The goal of this study is minimizing the fixed cost of constructing required facilities, transportation costs, and operational costs (harvesting, pretreatment, treatment, and energy conversion). This paper considers supply, production, distribution, and addresses a multi-period model. Since the volume of harvested and dried algae cannot be determined accurately, a fuzzy programming approach is employed to address uncertainties. Additionally, a data envelopment analysis (DEA) method is used to reduce the complexity of solving the proposed model. The applicability of the model is evaluated through a real case study of Iran.

Keywords: Biobutanol supply chain; Microalgae; Fuzzy approach; DEA method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:179:y:2019:i:c:p:1004-1016

DOI: 10.1016/j.energy.2019.04.219

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