چكيده لاتين
The increasing demand for energy and the limitation of fossil fuel resources, along with environmental concerns arising from greenhouse gas emissions, have made the focus on renewable energy sources more important than ever. Among these, the production of biofuels based on microalgae, due to its ability to absorb carbon dioxide, minimal land requirements, and the potential for producing valuable by-products, is considered one of the sustainable options for meeting future energy needs. The efficient design of the supply chain network for these biofuels, which can simultaneously address economic, environmental, and social dimensions, is an undeniable necessity.
In this research, a multi-objective mathematical model is proposed for designing the supply chain network of biofuels based on microalgae. The main objectives of the model include minimizing the total network costs, minimizing carbon dioxide emissions, and maximizing the social dimension through job creation. To make the model more realistic, the concept of resilience has been incorporated into the model to ensure that the network maintains its stability against disruptions such as power outages and equipment failures. Furthermore, the uncertainty in supply and demand is accounted for through a scenario-based robust optimization approach, and its control parameters are adjusted using sensitivity analysis.
For solving the model, several methods for generating the Pareto front, including epsilon constraint enhancement, two versions of Benson’s KKT , weighted sum, Pascoletti-Serafini, Tchebycheff, and its proposed version, were applied. Then, conventional metrics for assessing the quality of the Pareto front were calculated to evaluate the spread and convergence of the solutions, and finally, ranking was done using Shannon entropy and VIKOR.
Numerical results showed that the resilient sustainable model, compared to purely economic, green, and sustainable models, provides a more realistic balance between cost, emissions, and service level. The total costs in this model are 27.2% lower than the sustainable model, while the resilience of the network has significantly increased. Additionally, greenhouse gas emissions in this model are reduced by 21.2% compared to the economic model, 17.5% compared to the green model, and approximately 2% compared to the sustainable model. The inventory level has also decreased to 19,544.13 units and has been able to meet 40.4% of the total demand.
Furthermore, sensitivity analysis of conversion coefficients indicates that improving the efficiency of converting microalgae to lipids and lipids to biodiesel not only reduces the total costs but also decreases the movement in the network, and consequently, reduces transportation-related emissions.