Basic concepts of optimization, Convex sets and covex functions Simplex method, LP problem, slack variables Derivative-free optimization methods Fibonacci series and Golden Section, Brent method Gradient based methods, Quasi-newton methods Heuristic methods Constrained optimization : Primal and dual methods Multidisciplinary optimization problems Programming aspects Practical Work: exercises and labs on the design of optimisation algorithms on benchmark engineering problems. The students will be able to: Understand different theoretical and computational aspects of a wide range of optimization methods, Use of optimization toolbox.