A hybrid Metaheuristic Algorithm for Design and Optimization of Wastewater to Biodiesel Supply Chain in Iran

One of the most important challenges for the future energy supply of Iran is its dependence on oil resources and underdevelopment of renewable energies. In recent years, biofuel has been widely used as a substitute for fossil fuels around the world. Although the production of biofuels from food crops has been proved to be economically viable in some countries such as Brazil, due to its negative side-effects on agricultural markets it has been facing practical limitations. An alternative to solve this problem is using non-food crops such as corn pods to produce fuel. Urban wastewater containing a significant amount of lipid that could be used to produce biodiesel has grabbed a lot of attention in recent years. Moreover, this would partly solve the problem of sewage sludge burial which is a serious concern in wastewater treatment plants. In order to study the deployment of such fuels, this paper focuses on the design of a supply chain for the production of fuel from wastewater, which optimally integrates all supply chain stages including the supply and transfer of wastewater from refiners, converting them to fuel and distribution of fuel. Given the nonlinearity of the resulting model, exact algorithms fail to solve it. Therefore, a hybrid meta-analysis model based on GA and PSO algorithms has been developed. The hybrid algorithm has proved to be superior to GA and PSO algorithms. The results also indicate that although the fuel from wastewater is not currently cost competitive, but with removing the subsidy of fossil fuels in the future and improving the conversion rate of wastewater to fuel, it can compete with alternative fuels.