AKTU Optimization Techniques (BEE055) Syllabus PDF – B.Tech 3rd Year
Optimization Techniques BEE055
All syllabus, notes, question bank & PYQ for this subject
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- Semester 5
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Syllabus — Optimization Techniques
Download PDFBEE055 · 3 credits · L-T-P 3-0-0
Pre-requisites of course: Basic mathematics
Course Outcomes
Upon the completion of the course, the student will be able to:
| CO 1 | Understand the importance of optimization techniques in engineering applications | K2 |
| CO2 | Learn optimization methods for solving linear programming problems | K3 |
| CO3 | Learn optimization methods for solving nonlinear programming problems | K3 |
| CO4 | Be aware of the concept of simulation and modern methods of optimization | K3 |
| CO5 | Apply optimization techniques to electrical engineering problems | K4 |
KL- Bloom’s Knowledge Level (K , K , K , K , K , K ) 1 2 3 4 5 6 K – Remember K – Understand K – Apply K – Analyze K – Evaluate K – Create 1 2 3 4 5 6
Course Content
Unit I
Introduction to Optimization: Engineering application of Optimization, Statement of an optimization problem, Optimal problem formulation, Classification of optimization problem, Optimum design concepts: Definition of Global and Local optima using basic calculus concepts; Classical Optimization Techniques: Unconstrained Optimization - Single variable optimization, Constrained multivariable optimization with equality constraints - Lagrange multipliers method, Constrained multivariable optimization with inequality constraints - Kuhn-Tucker conditions.
Unit II
Linear Programming: Standard form of linear programming, Graphical solution, Simplex method, Big-M method, Duality theory, Decomposition principle, Transportation problem using North-West Corner rule and Least cost rule.
Unit III
Non-Linear Programming: Standard form of non-linear programming, One–Dimensional Minimization Methods - Unimodal function, Dichotomous search, interval halving method; Unconstrained Optimization Techniques - Univariate method, Steepest descent method; Constrained Optimization Techniques - Interior Penalty function method, Exterior penalty function method.
Unit IV
Simulation: Definition, types of simulation, General process of simulation, advantages & disadvantages of simulation.
Project Management Techniques: PERT and CPM Modern methods of Optimization: Genetic algorithm, working principle, fitness function, GA operators – crossover & mutation, comparison of GA with traditional methods.
Unit V
Case study (algorithm only): Economic load scheduling of power plant (without considering losses), maintenance scheduling of machines in manufacturing industry, fuzzy logic based speed control of DC machines.
Text Books
- S.S.Rao,"Optimization - Theory and Applications", Wiley-Eastern Limited.
- Ronald L. Rardin, "Optimization in Operations Research", Pearson Education, 2019
- D.E. Goldberg,"Genetic Algorithm in Search Optimization and Machine Learning ", Addision-Wesley Publication, 1989
- Kwang Y. Lee, Mohamed A. El-Sharkawi, “Modern heuristic optimization techniques, Theory and applications to power systems”, Wiley-Interscience
Reference Books
- David G. Luenberger,"Introduction of Linear and Non-Linear Programming ", Wesley Publishing Company.
- Polak,"Computational methods in Optimization ", Academic Press.
- Pierre D.A., "Optimization Theory with Applications", Wiley Publications.
- Kalyanmoydeb,"Optimization for Engineering Design: Algorithms and Examples", PHI Publication
- L.P. Singh,"Advanced Power System Analysis and Dynamics ", Wiley Eastern Limited.
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