Development of advanced mathematical programming methods for sustainable engineering and system biology

• Autores: Pavel Vaskan
• Directores de la Tesis: Laureano Jiménez Esteller (dir. tes.), Gonzalo Guillén Gosálbez (dir. tes.)
• Lectura: En la Universitat Rovira i Virgili ( España ) en 2014
• Idioma: inglés
• Tribunal Calificador de la Tesis: Moisès Graells Sobré (presid.), Dieter Boer (secret.), Rubén Ruiz Femenia (voc.)
• Materias:
  • Matemáticas
    • Investigación operativa
      • Programación entera
  • Ciencias tecnológicas
    • Ingeniería y tecnología químicas
    • Ingeniería y tecnología del medio ambiente
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • The main goal of this thesis is to develop advanced mathematical programming tools to address the design and planning of sustainable engineering systems and the modeling and optimization of biological systems. First we introduce a novel framework for the coupled use of Geographical Information Systems (GIS), Mixed-Integer Linear Programming (MILP) and decomposition algorithm for GIS based MILP models. Our approaches combine optimization tools, spatial decision support tools, economic and environmental analysis. Second we propose the general framework for sustainable design of energy systems like heat exchanger networks and utility plant. Our method is based on the combined use of the multi-objective optimization tools, Life Cycle Assessment methodology (LCA) and a rigorous dimensionality reduction method that allows identifying key environmental metrics. Finally we introduce multi-objective Mixed-Integer Non-Linear Programming (MINLP) based method for identifying in a rigorous and systematic manner the most probable biological objective functions explaining the operation of metabolic networks.