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Processe Strategy and Optimization

Code: EQ0037     Acronym: EOP

Keywords
Classification Keyword
OFICIAL Chemical Engineering

Instance: 2006/2007 - 2S

Active? Yes
Responsible unit: Department of Chemical and Biological Engineering
Course/CS Responsible: Master in Chemical Engineering

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
LEQ 0 Plano de estudos de transição para 2006/07 4 7,5 7,5 -
MIEQ 50 Syllabus since 2006/2007 4 - 7,5 -

Teaching language

Portuguese

Objectives

The use of simulation and optimization tools constitutes an undeniable advantage in conducting existing processes and developing new products and processes. Simple personal computers may be used with these adanced tools to attack problems of considerable size.
The main objective is to provide students with the necessary skills to attack process problems under their simulation and optimization points of view.
We hope that students gain aptitudes to establish information flow diagrams for large-scale systems, to formulate appropriate objective functions and constraints, and to obtain optimum solutions under an equation-oriented environment.

Program

General structure
Sensitivity analysis

System decomposition and local degrees of freedom.
Information flow diagrams vs. PFD
Decomposition algorithm of Lee, Christensen and Rudd.
Global degrees of freedom.
Persisten recycling.
MxMSGA algorithm.

Necessary stationarity conditions and N/S conditions for local minimum.
Lagrange multipliers and equality constraints.
KKT conditions for the general constrained problem.
N/S conditions for the global optimum. Convex functions and convex regions.

Univariate optimization: interval (golden section) and point (Powell) methods.

Unidirectional search in multivariate problems. Recurrent function.
Gradient-based methods
How to choose the optimum step size.
Second-order Newton-Raphson method.
Marcquart’s extension.
Hessian approximations.
Living with constraints (penalty functions and other)
Local minima and feasibility.

GAMS and Excel

Linear programming
Simplex method (geometric and algebraic)
Duality as a decision tool.

Mandatory literature

T.F. Edgar, D.M. Himmelblau, L.S. Lasdon,; Optimization of Chemical Processes, McGraw-Hill, 2001.

Complementary Bibliography

Romualdo L.R. Salcedo; Problemas de Optimização Não-linear (para resolução em computador), FEUP edições, 2001

Teaching methods and learning activities

Theoretical and problem resolution on every topic. Computer case studies.

Software

Excel, GAMS e MxMSGA

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description Type Time (hours) Weight (%) End date
Subject Classes Participação presencial
Total: - 0,00

Eligibility for exams

Cumulatively class attendance under legal terms and attendance grade (CF) at least 10/20.
Evaluation components (graded for 20)
• Attendance grade (CF) obtained by weightr average of home work by group of 4 students (CTG) + teacher opinion during classes(OP).
• Writen individual exam (EFEI) with allowed bibliography, using calculators, for a maximum of 2.5 hours.

Calculation formula of final grade

How to calculate attendance grade (CF) and final grade(CLASS_FINAL)
• CF = 0,80 * CTG + 0,20 * OP
• CLASS_FINAL = 0,50 * CF + 0,50 * EFEI

Examinations or Special Assignments

Group work to be performed on week 14.05 and delievery on 29.05

Classification improvement

Individual and global exam, similar in structure, but not in content, to the final individual test.
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