An economic analysis for integrated bi-objective biofuel supply chain design using support vector machine

Abstract

Using second-generation biomass and biofuel deal with environmental pollution and CO₂ emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO₂ emissions. The economic analysis consists of three scenarios for supplying biomass. The SVM method specifies the potential place to build the bio-refinery. The next step solves the model with the augmented ε-constraint method. Finally, results show that biomass production and imports simultaneously reduce costs by 24.5% compared to the production scenario and 4.3% compared to the import scenario. According to the results obtained, despite the increase in cost, it reduces the amount of CO₂ emissions. So, the Pareto solution resulted from the augmented ε-constraint method for the problem is determined as one of the most effective techniques to help the decision-makers.