Metaheuristic for Solving a Two-stage Stochastic Biofuel Hub-and-Spoke Network Problem

摘要

An alternative to the production of fossil transportation fuels is the production of biofuels, specifically, bioethanol. One of the main areas of opportunity is the reduction of the biofuel overall cost. An approach to reduce this cost is to design and implement a supply chain (SC) that takes into consideration the quality-related properties of the biomass as well as the economies of scale to minimize the logistics and quality-related costs. The design of the SC consists of identifying the best locations to open depots to store and preprocess the biomass and the facilities to convert biomass into biofuel, as well as the flows of biomass between the aforementioned facilities. This problem is formulated as the hub location problem, which has been classified as an NP-hard problem. Therefore, meta-heuristics are a suitable approach to solve this problem. We propose a two-stage hybrid meta-heuristic solution procedure to solve large-scale instances of a two-stage stochastic biomass-to-biorefinery hub-and-spoke network problem. This solution procedure is proposed to support the large-scale production and distribution of bioethanol derived from non-edible feedstock such as switchgrass by taking into consideration the variability in their moisture and ash contents. The hybrid method utilizes a Simulated Annealing-Simplex solution procedure to find an initial solution and a Tabu Search-Simplex method to improve the solution. Numerical experimentation has been performed on a realistic case study in Texas. The results show that the hybrid procedure outperforms the standard L-shape (LS) method. The meta-heuristic combining Simulated Annealing and Tabu Search with the Simplex method (SATS-SM) has found lower costs by 0.43% and better time by 99.96%, on average, when compared to the results from using the LS.