Optimization in Rubber Industries(OPTRI)
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Follow on Instagram for UpdatesOptimization in Rubber Industries(OPTRI) Syllabus — Unit-wise Content
The official GTU curriculum for Optimization in Rubber Industries(OPTRI) (subject code 2724003) as prescribed for RE · Semester 2 divides the course into 6 units, covering 47 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 (2724003)Unit 1 Introduction to Optimization
- Basic concept of optimization
- formulation of optimization problems
- problem dressing
- feasible region
- Classification of Optimization Problems: single variable- multivariable problems
- optimization without constraints - with constraints
- Maximization and minimization problems
- Convex and concave functions
- single objective-multiobjective optimization
Unit 2 Analytical Optimization Techniques
- Stationary points
- Optimization of unconstrained Functions One-dimensional Search
- direct substitution
- constrained variation
- penalty function
- Lagrangian Multiplier
- Kuhn-Tucker theorem
- Simplex Method of Linear Programming
- Duals in optimization
- Quadratic programming
- Geometric Programming
Unit 3 Numerical Optimization Techniques
- General principles of numerical search
- region elimination techniques
- direction of search
- final stage in search
- direct search
- pattern search
- acceleration in direct search
- gradient methods
- the complex method of Box
Unit 4 Application of Optimization In Rubber Industries
- Design of product mixes
- optimization in mould design
- product shape-size design
- screw design
- optimization in Mixing
Unit 5 Optimal design and scheduling
- Single product batch plants
- Multiple product batch plants
- Parallel units and intermediate storage
- Sizing in batch plants
- flow shop and jobshop plants
- constraints and formulation of design models for optimization
- formulations for discrete sizes
Unit 6 Advanced Optimization Techniques
- Genetic Algorithm
- Mematic Algorithm
- Simulated Annealing
- Differential Evolution
- Ant Colony Optimization
- Particle Swam Optimization and recent developments
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