Chemical Process Optimization
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Follow on Instagram for UpdatesChemical Process Optimization Syllabus — Unit-wise Content
The official GTU curriculum for Chemical Process Optimization (subject code ME02072041) as prescribed for CAPD · Semester 2 divides the course into 8 units, covering 57 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME02072041)Unit 1 Optimization
- Basic concept of optimization
- Mathematical formulation of optimization problems
- Classification of Optimization Problems - single variable problems
- Multivariable problems without constraints
- Multivariable problems with constraints
- Maximization and minimization problems
- Convex and concave functions & determination
- Necessary and sufficient conditions for stationary points
Unit 2 Optimization of Unconstrained Functions
- Single variable Search: Analytical methods
- Numerical methods
- scanning and bracketing techniques
- region elimination techniques
- exhaustive search
- interpolation methods – with & without derivatives
- comparison of various methods
Unit 3 Optimization of Unconstrained Functions
- Multivariable Search – Analytical Methods: Classification
- Without derivatives - Random search
- grid search
- Univariate search
- With derivatives – Newtons method
Unit 4 Optimization of Unconstrained Functions
- Multivariable Search – Numerical Methods: general principles of numerical search
- direction of search
- final stage in search
- direct search
- pattern search
- acceleration in direct search
- gradient methods
- Simplex search
- Powells method
- Box complex method
- Quasi-Newton methods
Unit 5 Optimization of Constrained Functions
- Linear Programming (LP) and its applications: Basic linear programming
- formulation of LP problem
- Solution of LPP by graphical technique
- Simplex algorithm
- Primal- Dual relation
Unit 6 Optimization of Constrained Functions
- Non- Linear Programming (NLP) and its applications: Lagrangian Multiplier method
- Kuhn-Tucker theorem
- penalty function
- Quadratic programming
- Geometric Programming
- Dynamic programming
- Integer and mixed integer programming
Unit 7 Application of Optimization In Chemical Engineering
- Optimum vessel sizing
- optimum insulation
- Optimal pipe diameter
- Optimum work of compression
- Optimal shell-tube heat exchanger design
- optimal design of distillation column
- Optimal design of an Ammonia reactor and other applications
Unit 8 Non-traditional Optimization Techniques
- Genetic Algorithm
- Simulated Annealing
- Ant Colony Optimization
- Particle swarm optimization
- TABU search
- Multi Objective Optimization
- Selection of techniques
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