A decomposition approach based on meta-heuristics and exact methods for solving a two-stage stochastic biofuel hub-and-spoke network problem

Abstract

An alternative to the production of fossil transportation fuels is the production of biofuels, specifically, bioethanol. One of the main opportunity areas is the reduction in the overall cost of biofuel. An approach to reduce this cost is to design and implement a supply chain (SC) that considers the quality-related properties of the biomass as well as the economies of scale to minimize the logistics and quality-related costs. This problem is formulated as a 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 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 by considering the variability in its moisture and ash contents. The hybrid method utilizes a simulated annealing-simplex method to find an initial solution and a tabu search-simplex method to improve the solution. Numerical experimentation was performed on a realistic case study in Texas. The results show that the hybrid procedure outperforms the standard L-shaped (LS) method. The meta-heuristic combining simulated annealing and tabu search with the simplex method (SATS-SM) achieved 2.48% lower costs and required 96.57% less time, on average, when compared to the results from using the LS.