Strategic Planning for the Sustainable Production of Biofuels presents several optimization models for the design and planning of sustainable biorefinery supply chains, including issues surrounding the potential of biomass feedstocks in multiple harvesting sites, availability and seasonality of biomass resources, different potential geographical locations for processing plants that produce multiple products using diverse production technologies, economies of scale for production technologies, demands and prices of multiple products, locations of storage facilities, and a number of transportation modes. Sustainability considerations are incorporated into the proposed models by including simultaneous economic, environmental and social performance in the evaluation of the supply chain designs.

This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus (R), HYSIS (R), Super Pro Designer (R) linked to a variety of metaheuristic techniques implemented in Matlab (R), Excel (R), C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab (R) routines are included as electronic supporting material.

This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus (R), HYSIS (R), Super Pro Designer (R) linked to a variety of metaheuristic techniques implemented in Matlab (R), Excel (R), C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab (R) routines are included as electronic supporting material.