|Course Tutors||Dr Sofia Simaria|
Three-hour written exam (65%)
Two case study reports (35%)
|Prerequisites||Project Appraisal for Bioprocesses (BENG 3006), Computer Aided Bioprocess Engineering (BENG 3009), Fermentation and Bioreactor Engineering (BENG 2010), Bioprocess Recovery and Purification (BENG 2011) or courses with similar content.|
This course is designed to provide students with skills in advanced modelling, optimisation and statistical techniques such that they are adequately equipped to address problems related to evaluating the cost-effectiveness and robustness of alternative bioprocess design strategies.
Computer lab sessions: 20h
- Discrete-event simulation Introduction to queuing systems; Basic concepts of discrete-event simulation; Use of simulators.
- Uncertainty analysis Identification of sources of uncertainty and variability in bioprocessing; Monte Carlo simulation to address uncertainty
- Multi-criteria decision-making Basic concepts; Weighted sum method; Generation of non-dominated solutions/Pareto front
- Optimisation: mathematical programming Linear programming (LP) formulation; Graphical, simplex method and sensitivity analysis; Mixed integer linear programming (MILP) formulation and branch-and-bound method.
- Optimisation: meta-heuristic approaches Combinatorial optimisation: typical problems and bioprocess-related examples; Constructive heuristics, local search and local optimality; Meta-heuristics: overview of most popular methods; Application of genetic algorithms to bioprocessing problems
- Research showcase’ Presentation of current (or past) research within the Decisional Tools group directly linked with the subjects taught.