update_params.m
4f9ff70f0445master

update_params.m
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			function [beta_, sigma_, k_t] = update_params(feas_cur, feas_old, k_t, iter, beta_old, sigma_old, sigma_vec, beta_vec, sigma_0, beta_0)
			% This function computes the parameters for the new iteration depending on
			% the predefined adaptive rule
			% INPUTS: feas_cur: current feasibility value
			% iter : current iteration number
			% sigma_0 : initial value for the dual step size
			% beta_0 : initial value for the penalty parameter
			% OUTPUTS: beta_ : updated penalty parameter
			% sigma_ : updated dual step size
			%
			% Author: Mehmet Fatih Sahin
			% Date: 09.11.2018

			if iter<2
			beta_ = beta_0;
			sigma_ = sigma_0;
			return
			end

			if feas_cur > beta_0/sqrt(iter)
			beta_ = beta_old*sqrt(iter/(iter-1));
			else
			beta_ = beta_old;
			end

			if feas_old <= sigma_0/sqrt(iter) && feas_cur > sigma_0/sqrt(iter)
			k_t = iter;
			end

			if feas_cur <= sigma_0/iter
			sigma_ = sigma_old;
			elseif sigma_0/iter < feas_cur && feas_cur<=sigma_0/sqrt(iter)
			sigma_ = sigma_old*sqrt((iter-1)/iter);
			else
			% sigma_ = sigma_0/beta_0*(beta_-beta_old);
			if k_t == iter
			sigma_ = sigma_old;
			elseif k_t == 1
			sigma_ = sigma_old/beta_0*(beta_-beta_old);
			else
			sigma_ = sigma_vec(k_t)/(beta_vec(k_t)-beta_vec(k_t-1))*(beta_-beta_old);
			end
			end


			end