A SAL based algorithm for convex optimization problems

A new successive approximation logic (SAL) based iterative optimization algorithm for convex optimization problem is presented in this paper. The algorithm can be generalized for multi-variable quadratic objective function. There are two major advantages of the proposed algorithm. First of all, the proposed algorithm takes a fixed number of iterations which depends not on the objective function but on the search span and on the resolution we desire. Secondly, for an n variable objective function, if the number of data points we consider in the span is N, then the algorithm takes just n log₂ N number of iterations.