Integrated strategic, tactical and operational planning of sugarcane-based biomass to biofuel supply chains : a hybrid optimization-surrogate approach

Overview & Synopsis

In recent years, research has focused heavily on the production of biofuel from biomass due to its potential as a renewable energy source, its high potential to replace the high cost of fossil fuels, and the environmental concerns associated with its excessive consumption. However, to effectively provide a biofuel product that can compete in the market, the establishment of resilient supply chain planning is important. Therefore, supply chain planning that considers a holistic approach is essential to improving the efficiency of the biofuel supply chain.In the literature, biofuel supply chain planning has been done hierarchically at the strategic (long-term decisions: supply network design), tactical (medium-term decisions: management of network design), and operational (short-term decisions: routing) levels by developing distinct models. The problem with the hierarchical method is that using solutions from one level may result in inconsistent or infeasible solutions. This is because each lower planning level (tactical and operational) includes variations that are not accountable at higher planning levels (strategic). However, integrating the three decision levels frequently leads to large mixed-integer linear or non-linear problems that require enormous computational effort to solve. Thus, a method that can overcome the computational problem is required. Therefore, the main goal of this dissertation is to accurately integrate the different decision levels and study the impact of the decision across these scales by maximizing the economic benefits and minimizing the environmental impacts across the biofuel supply chain.This work addresses a holistic approach to supply chain optimization by integrating the three decision levels (strategic, tactical, and operational). Firstly, an optimization model that integrates strategic and tactical decisions is developed in the first stage, and a vehicle routing problem is developed as an operational model in the second stage. To optimally solve the optimization model with the operational model, a novel sequential iterative approach is designed. The optimization model is mixed-integer linear programming (MILP) that maximizes the NPV of the bioethanol supply chain, while the operational model is a vehicle routing problem (VRP) that minimizes the transportation cost. Secondly, an effort is made to incorporate environmental perspectives into the integrated strategic and tactical plan of the biomass-to-biofuel supply chain, coupled with the operational plan. This is achieved by incorporating an environmental objective that quantifies the greenhouse gas (GHG) emissions associated with the supply chain. The environmental performance of the biofuel supply chain is assessed using a life cycle assessment (LCA) of the system and converted into monetary value by adopting an eco-cost approach. The developed approach is applied to optimize the biofuel supply chain in Ethiopia's biofuel sector, overcome the computational complexity associated with solving the underlying large-scale mixed integer linear problem, and provide a better representation of supply chain reality. The result of this research highlights the contribution of the operational level in enhancing the quality, coherence, and relevance of the results, as well as their impact on the strategic and tactical levels.