University of Mumbai Syllabus For Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques: Knowing the Syllabus is very important for the students of Semester 4 (SE Second Year). Shaalaa has also provided a list of topics that every student needs to understand.
The University of Mumbai Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques syllabus for the academic year 2022-2023 is based on the Board's guidelines. Students should read the Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques Syllabus to learn about the subject's subjects and subtopics.
Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the University of Mumbai Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques Syllabus pdf 2022-2023. They will also receive a complete practical syllabus for Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques in addition to this.
University of Mumbai Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques Revised Syllabus
University of Mumbai Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques and their Unit wise marks distribution
University of Mumbai Semester 4 (SE Second Year) Numerical Methods and Optimization Techniques Course Structure 2022-2023 With Marking Scheme
Syllabus
- Error Analysis: Types, estimation, error propagation.
- Roots of equation: Bracketing Methods- The bisection method, the false-position method, Open methods-The Newton-Raphson method, The secant method, Systems of Nonlinear EquationsNewton Raphson method.
- Application for the design of an electric circuit.
- Linear Algebraic Equations: LU Decomposition, Solution of currents and voltages in Resistor circuits.
- Curve Fitting: Interpolation with Newton’s divided- difference interpolating polynomials, Lagrange interpolating polynomials, Coefficients of interpolating polynomials, Inverse interpolation, curve fitting with sinusoidal functions.
- Solution of ordinary differential equation: Predictor –corrector methods, Milne’s method, Adams-Bashforth method, solution of simultaneous first order & second order differential equations by Picard’s and Runge-Kutta methods.
- Simulating transient current for an electric circuit.
- One dimensional unconstrained Optimization: Golden-section search, quadratic interpolation, Newton’s method.
- Constrained Optimization: Introduction of L.P.P., Formulation of the L.P.P., Canonical and Standard forms of L.P.P., solution of L.P.P. by Graphical Method, Introduction to Simplex Method, General Linear Programming Problem, Procedure of simplex method.
- Non-linear programming: Introduction, Single variable optimization, Multivariable optimization with equality constraint-Lagrange’s method, Multivariable optimization with non-equality constraint- Kuhn-Tucker conditions
