Andrea Zamboni

Spatially explicit multi-objective optimisation for design and planning of hybrid first and second generation biorefineries

Abstract Climate change mitigation has become a binding driver in biofuels production. First generation bioethanol, initially indicated as the most competitive option, is now incurring in ever increasing discredits forcing the transition towards more sustainable productions (i.e. second and third generation technologies). This paper addresses the strategic design and planning of corn grain- and stover-based bioethanol supply chains through first and second generation technologies. A Mixed Integer Linear Programming framework is proposed to optimise the environmental and financial performances simultaneously. Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach. A demonstrative case study is proposed involving the future Italian biomass-based ethanol production. Results show the effectiveness of the optimisation tool at providing decision makers with a quantitative analysis assessing the economic and environmental performance of different design configuration and their effect in terms of technologies, plant sizes and location, and raw materials.

Capacity planning and financial optimization of the bioethanol supply chain under price uncertainty

This work addresses the development of a dynamic spatially explicit MILP (Mixed Integer Linear Programming) modeling framework devised to optimize the design and planning of biomass-based fuel supply networks according to financial criteria and accounting for uncertainty on market conditions. The model capabilities in steering strategic decisions are assessed through a real-world case study related to the emerging corn-based bioethanol production system in Northern Italy. Two optimization criteria are considered, based on a risk-seeking or, alternatively, on a risk-adverse-approach.

Supply Chain Optimization for Bioethanol Production System in Northern Italy: Environmentally Conscious Strategic Design

Abstract This work proposes a spatially explicit modeling framework developed for the strategic design of biomass-based fuel supply networks. A Mixed Integer Linear Programming (MILP) model is formulated and solved for the multi-objective optimization of the whole supply network in terms of both operating costs and greenhouse gas (GHG) emissions. The economics are assessed by means of Supply Chain Analysis (SCA) techniques. The environmental performance is evaluated in terms of greenhouse gas emissions, by adopting a Well-to-Tank (WTT) approach. The framework capabilities in steering the strategic design path are assessed through a real-world case study.

Towards second generation bioethanol: Supply chain design and capacity planning.

Abstract This work proposes a multi-period and spatially explicit framework conceived to drive strategic policies on biofuels. A Mixed Integer Linear Programming (MILP) model is proposed as quantitative tool to optimise the oncoming transition towards more sustainable infrastructures. This paper addresses the design of bioethanol supply chains where both corn grain and stover are considered as suitable biomass. A Mixed Integer Linear Program is proposed to optimise the system financial performance and to comply with EU environmental regulation by taking into account a wide number of technological options. Bioethanol production in Northern Italy is chosen as a demonstrative case study.

Environmentally conscious supply chain design and capacity planning: From first to second generation biofuel systems.

Supply Chain optimisation tools may help managing the oncoming transition from first to second generation bioethanol productions. A multi-objective Mixed Integer Linear Programming is developed to design bioethanol supply chains where both corn grain and stover are considered as suitable biomass. Environmental and financial performance are simultaneously taken as design drivers and alternative process design options are considered, too. Northern Italy is taken as geographical benchmark to assess a realworld case study. Results show how the design transition from first to second generation bioethanol systems substantially depends on the specific trade-off between environmental and financial objectives.