PC3007 Optimization of Chemical Processes Syllabus:
PC3007 Optimization of Chemical Processes Syllabus – Anna University Regulation 2021
OBJECTIVE:
The course is aimed to develop objective functions and use linear programming, geometric, dynamic and integer programming and genetic algorithms for solution to chemical engineering problems.
UNIT I
Introduction to optimization; applications of optimization in chemical engineering; classification of Optimization problems; Developing models for optimization
UNIT II
Continuity of Functions; NLP Problem Statement Convexity and Its Applications Interpretation of the Objective Function in Terms of its Quadratic Approximation Necessary and Sufficient Conditions for an Extremum of an Unconstrained Function; region elimination methods; interpolation methods; direct root methods.
UNIT III
Methods Using Function Values Only -Random Search -Grid Search – Univariate Search – Simplex Search Method – Conjugate Search Directions; Methods That Use First Derivatives – Steepest Descent – Conjugate gradient Methods; Newton’s Method and Quasi Newton’s Method
UNIT IV
Introduction to geometric, dynamic and integer programming and genetic algorithms. Linear Programming – Solution of Problems using Excel SOLVER
UNIT V
Formulation of objective functions; fitting models to data; applications in fluid mechanics, heat Transfer, mass transfer, reaction engineering, equipment design, reaction engineering, resource allocation and inventory control.
TOTAL: 45 PERIODS
COURSE OUTCOMES:
On the completion of the course students are expected to
CO1: Frame mathematical models and formulate optimization models for chemical processes / equipment.
CO2: Understand the concept of optimum and extremum and the necessary and sufficient Conditions for extremum and solve single and multivariable optimization problems through various techniques.
CO3: Apply various search methods to solve unconstrained single variable optimization and Unconstrained multi variable optimization
CO4: Apply higher order techniques like geometric programming, dynamic and integer programming and genetic algorithms
CO5: Able to use the principles of engineering and in particular chemical engineering to develop equality and inequality constraints for an optimization problem
CO6: Apply optimization techniques for real world problems and be knowledgeable to use Software packages for their solution
TEXT BOOKS:
1. Rao, S. S., Engineering Optimization – Theory and Practice, Third Edition, John Wiley & Sons, New York, 1996.
2. Edgar, T.F., Himmelblau, D.M., “Optimisation of Chemical Processes “, McGraw-Hill Book Co., New York, 2003.
3. Reklaitis, G.V., Ravindran, A., Ragsdell, K.M. “Engineering Optimisation “, John Wiley, New York, 1980.
REFERENCES:
1. Venkataraman, P. (2009). Applied optimization with MATLAB programming. John Wiley & Sons.
2. Ferris, M. C., Mangasarian, O. L., & Wright, S. J. (2007). Linear programming with MATLAB (Vol. 7). SIAM.
3. J Nocedal and S J Wright (2006). Numerical Optimization. Springer Verlag.
4. Joshi, M. C., & Moudgalya, K. M. (2004). Optimization: theory and practice. Alpha Science Int’l Ltd..