JNTUH B.Tech 4th year (4-1) Optimization Techniques gives you detail information of Optimization Techniques (Elective-II) R13 syllabus It will be help full to understand you complete curriculum of the year.<\/p>\n
Objective<\/strong><\/p>\n This course introduces various optimization techniques i.e classical, linear programming, transportation problem, simplex algorithm, dynamic programming, Constrained and unconstrained optimization techniques for solving and optimizing an electrical and electronic engineering circuits design problems in real world situations.<\/p>\n UNIT-I<\/strong><\/p>\n Introduction & Classical Optimization Techniques: Statement of an Optimization problem \u2014 design vector \u2014 design constraints \u2014 constraint surface \u2014 objective function \u2014 objective function surfaces \u2014 classification of Optimization problems Single variable Optimization \u2014 multi variable Optimization without constraints \u2014 necessary and sufficient conditions for minimum\/maximum multivariable Optimization with equality constraints. Solution by method of Lagrange multipliers \u2014 multivariable Optimization with inequality constraints \u2014 Kuhn \u2014 Tucker conditions.<\/p>\n UNIT \u2014 II<\/strong><\/p>\n Linear Programming: Standard form of a linear programming problem \u2014 geometry of linear programming problems \u2014 definitions and theorems \u2014 solution of a system of linear simultaneous equations \u2014 pivotal reduction of a general system of equations \u2014 motivation to the simplex method \u2014 simplex algorithm.<\/p>\n UNIT – III<\/strong><\/p>\n Transportation Problem & Unconstrained Optimization: Finding initial basic feasible solution by north \u2014 west corner rule, least cost method and Vogel\u2019s approximation method testing for optimality of balanced transportation problems, One dimensional minimization methods: Classification, Fibonacci method and Quadratic interpolation method. Univariate method, Powell\u2019s method and steepest descent method.<\/p>\n