Syllabus Eighth Semester Optimization Technique ME-8004
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 Eighth Semester Optimization Technique ME8004 is given here.
The objective of this course “Syllabus Eighth Semester Optimization Technique ME8004“ 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 8004 – Optimization Technique
Dynamic programming, introduction, posynomial, geometrical programming, unconstraint/ constraint minimization, applications of geometric programming, multistage decision processes, suboptimization and principles of optimality, computational procedures, linear programming as a case of dynamic programming, continuous dynamic programming, design of continuous beam, trusses.
Integer linear and non linear programming, graphical representation, stochastic programming, Introduction to genetic algorithm, neural network based optimization, practical aspect of optimization.
Books Recommended
1. S.S. Rao, Engineering optimization, New Age International Publishers, ISBN: 81 224 1149 5
2. A. Ravindran, K. Ragsdell and G. Reklaitis, Engineering Opimization, John wiley &Sons
3. K. Deb, Optimization for Engineering Design, Prentice Hall of India.
