OPTIMIZATION TECHNIQUES Course Code: MTE 304 Credit Units: 04 Course Objective: In a fast changing environment an understanding is required which will provide facility to implement a problem for minimum cost, greater efficiency better customer service and higher quality. Optimization Techniques gives us help in solving such type of problems. Course Contents: Module I: Introduction to Optimization Statement of an optimization problem, Classification of optimization problems, Optimization techniques, Engg. applications of optimization. Module II: Classical Optimization Techniques Single variable optimization, Multivariable optimization with no constraints, Multivariable optimization with equality constraints, Multivariable optimization with in equality constraints. Module III: Linear Programming Standard form of linear programming, Graphical solution, Simplex method, Two-phase simplex method, Computer implementation of the simplex method, Duality theory. Module IV: Transportation Problem North-West Corner rule, Least cost method, Vogel approximation method, testing for optimality. Module V: Non-Linear Programming: One–dimensional minimization methods Unimodal function, Dichotomous search, Fibonacci search, Quadratic interpolation method, Cubic interpolation method. Module VI: Non-Linear Programming-Unconstrained Optimization Techniques Random search method, steepest descent method, Conjugate gradient method, Variable metric method. Module VII: Non-Linear Programming - Constrained Optimization Techniques Interior Penalty function method, Exterior penalty function method. Further Topics in Optimization Critical path method (CPM), Program evaluation and review technique (PERT). Examination Scheme: Components A CT S/V/Q HA EE Weightage (%) 5 10 8 7 70 CT: Class Test, HA: Home Assignment, S/V/Q: Seminar/Viva/Quiz, EE: End Semester Examination; Att: Attendance Text & References: S.S. Rao, Optimization: Theory and applications, Wiley Eastern Ltd. G.V. Reklaitis, Engg. Optimization Methods & applications, Wiley.
Course Objective: In a fast changing environment an
understanding is required which will provide facility to implement
a problem for minimum cost, greater efficiency better customer
service and higher quality. Optimization Techniques gives us help
in solving such type of problems. Course Contents: Module I:
Introduction to Optimization Statement of an optimization problem,
Classification of optimization problems, Optimization techniques,
Engg. applications of optimization. Module II: Classical
Optimization Techniques Single variable optimization, Multivariable
optimization with no constraints, Multivariable optimization with
equality constraints, Multivariable optimization with in equality
constraints. Module III: Linear Programming Standard form of linear
programming, Graphical solution, Simplex method, Two-phase simplex
method, Computer implementation of the simplex method, Duality
theory. Module IV: Transportation Problem North-West Corner rule,
Least cost method, Vogel approximation method, testing for
optimality. Module V: Non-Linear Programming: Onedimensional
minimization methods Unimodal function, Dichotomous search,
Fibonacci search, Quadratic interpolation method, Cubic
interpolation method. Module VI: Non-Linear
Programming-Unconstrained Optimization Techniques Random search
method, steepest descent method, Conjugate gradient method,
Variable metric method. Module VII: Non-Linear Programming -
Constrained Optimization Techniques Interior Penalty function
method, Exterior penalty function method. Further Topics in
Optimization Critical path method (CPM), Program evaluation and
review technique (PERT). Examination Scheme: Components A CT S/V/Q
HA EE Weightage (%) 5 10 8 7 70 CT: Class Test, HA: Home
Assignment, S/V/Q: Seminar/Viva/Quiz, EE: End Semester Examination;
Att: Attendance Text & References:
S.S. Rao, Optimization: Theory and applications, Wiley Eastern
Ltd. G.V. Reklaitis, Engg. Optimization Methods & applications,
Wiley.
