Requirement of maths teacher who can teach 2nd year computer science engineering students mathematics.
Budget: ₹100 – ₹400 INR
Requirement of maths teacher who can teach 2nd year students engineering mathematics.
SYLLABUS TO BE TAUGHT :
UNIT-I
Chapter-1 (Introduction to Optimization and Techniques)
Engineering application of optimization, statement and classification of optimization problems, optimization techniques. Single variable optimization, multi variable optimization with no constraint’s multivariable optimization with equality and inequality constraints.
Chapter-2 (Linear Programming)
Introduction and formulation of models, Convexity, Simplex method, Big-M method, Two-phase method, Degeneracy and unbounded solutions.
UNIT-II
Chapter-3 (Dual Linear Programming)
Duality in LPP, dual simplex method, transportation and assignment problems, traveling salesman problem.
Chapter-4 (Non-linear Programming)
Introduction, unimodes function, elimination methods, unrestricted search, quadratic and cubic interpolation methods, Direct root method, Direct and Random Search method, The simplex method, Steepest Descent method, Conjugate gradients method and Gauss-newton method.
UNIT-III
Chapter-5 (Dynamic Programming)
Stage space, recursive optimization, Principle of optimality.
Chapter-6 (Integer and Stochastic Programming)
Introduction to Integer linear programming, Knapsack problem, linear 0-1 problem, Methods for solving integer linear programming problems, stochastic linear programming, Quadratic programming separable programming.
NOTE: Only Indian freelancers are eligible.
SYLLABUS TO BE TAUGHT :
UNIT-I
Chapter-1 (Introduction to Optimization and Techniques)
Engineering application of optimization, statement and classification of optimization problems, optimization techniques. Single variable optimization, multi variable optimization with no constraint’s multivariable optimization with equality and inequality constraints.
Chapter-2 (Linear Programming)
Introduction and formulation of models, Convexity, Simplex method, Big-M method, Two-phase method, Degeneracy and unbounded solutions.
UNIT-II
Chapter-3 (Dual Linear Programming)
Duality in LPP, dual simplex method, transportation and assignment problems, traveling salesman problem.
Chapter-4 (Non-linear Programming)
Introduction, unimodes function, elimination methods, unrestricted search, quadratic and cubic interpolation methods, Direct root method, Direct and Random Search method, The simplex method, Steepest Descent method, Conjugate gradients method and Gauss-newton method.
UNIT-III
Chapter-5 (Dynamic Programming)
Stage space, recursive optimization, Principle of optimality.
Chapter-6 (Integer and Stochastic Programming)
Introduction to Integer linear programming, Knapsack problem, linear 0-1 problem, Methods for solving integer linear programming problems, stochastic linear programming, Quadratic programming separable programming.
NOTE: Only Indian freelancers are eligible.