Syllabus Sixth Semester Optimisation Techniques ME-604
The concepts developed in this course will aid in quantification of several concepts in Mechanical Engineering that have been introduced at the Engineering courses. Technology is being increasingly based on the latest Syllabus Sixth Semester Optimisation Techniques ME604 is given here.
The objective of this course “Syllabus Sixth Semester Optimisation Techniques ME604“ is to develop ability and gain insight into the process of problem-solving, with emphasis on thermodynamics. Specially in following manner: Apply conservation principles (mass and energy) to evaluate the performance of simple engineering systems and cycles. Evaluate thermodynamic properties of simple homogeneous substances. Analyze processes and cycles using the second law of thermodynamics to determine maximum efficiency and performance. Discuss the physical relevance of the numerical values for the solutions to specific engineering problems and the physical relevance of the problems in general and Critically evaluate the validity of the numerical solutions for specific engineering problems. More precisely, the objectives are:
- To enable young technocrats to acquire mathematical knowledge to understand Laplace transformation, Inverse Laplace transformation and Fourier Transform which are used in various branches of engineering.
- To introduce effective mathematical tools for the Numerical Solutions algebraic and transcendental equations.
- To acquaint the student with mathematical tools available in Statistics needed in various field of science and engineering.
ME 604 – Optimisation Techniques
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 – Optimality criteria – Review of basic calculus concepts – Global optimality.
Review of Linear programming methods for optimum design – Post optimality analysis – Application of LPP models in design and manufacturing.
Gradient based method: Cauchy’s steepest descent method, Newton’s method, Conjugate gradient method.
Optimization algorithms for solving constrained optimization problems:
Direct methods – penalty function methods – steepest descent method – Engineering applications of constrained and unconstrained algorithms.
Modern methods of Optimization:
Genetic Algorithms – Simulated Annealing – Ant colony optimization – Tabu search – Neural-Network based Optimization – Fuzzy optimization techniques – Applications. Use of Matlab to solve optimization problems.
Books Recommended
1. Rao S. S. – ‘Engineering Optimization, Theory and Practice’ – New Age International Publishers – 2012 – 4th Edition.
2. Deb K. – ‘Optimization for Engineering Design Algorithms and Examples’ – PHI – 2000
3. Arora J. – ‘Introduction to Optimization Design’ – Elsevier Academic Press, New Delhi – 2004
4. . Saravanan R. – ‘Manufacturing Optimization through Intelligent Techniques’ – Taylor & Francis (CRC Press) – 2006
5. Hardley G. -‘Linear Programming’ – Narosa Book Distributors Private Ltd. – 2002.
