% =========================================================================% Copyright (c)2006， 東南大學移動通信國家重點實驗室% All rights reserved.%% 文件名稱：SQP_Optimization_Gini.m% function描述：自編SQP的最優折中曲線搜索，Gini Index% 當前版本： 1.0% 作    者：梁浩% 完成日期： 2007年6月%==========================================================================function [op_th op_fair op_w] = SQP_Optimization_Gini(N, aimFair, mean, sigma)precision = 10.^(-6);epsilon_g = 100;               % 放松對梯度的要求，因為最大值點不一定是局部的極大值點epsilon_F = 10 .^ (-4);% 步驟(i)iter_num = 0;w = 1 .* ones(1, N-1);% 步驟(ii)[T F] = T_F_w_Gini(w, N, aimFair, mean, sigma);[g A] = g_A_w_Gini(w, N, aimFair, mean, sigma, precision);lambda = A' \ g';[x,fval,exitflag,output,grad,W] = W_w_lambda_Gini(N, aimFair, mean, sigma, lambda);        % 用fmincon求初始時刻的Hessian矩陣：W[T F g A S] = T_F_g_A_S_w_Gini(w, N, aimFair, mean, sigma, lambda, precision);                          % 求目標函數、限制函數和Lagrangian函數的梯度% % 步驟(iii)－(x)的循環while 1% % %     abs(g)% % %     abs(F)    if (sum(abs(g))<epsilon_g) && (abs(F)<epsilon_F)        break    end    mat_for_solving_A = W;    [size_row size_col] = size(mat_for_solving_A);    mat_for_solving_A(size_row+1,:) = A;    mat_for_solving_A(:,size_col+1) = [A, 0]';    mat_for_solving_b = -[g+lambda.*A, F]';    solution = mat_for_solving_A \ mat_for_solving_b;        delta_w = solution(1:length(solution)-1);    delta_lambda = solution(length(solution));        S_old = S;                     % 記錄當前狀態，以便于計算delta_S        w = w + delta_w';    lambda = lambda + delta_lambda';        % 更新參數    [T F g A S] = T_F_g_A_S_w_Gini(w, N, aimFair, mean, sigma, lambda, precision);    g     A     S    T     F         delta_S = S - S_old;        % 更新Hsessian矩陣% % %     W = W - W * delta_w * (W * delta_w)' ./ (delta_w' * W * delta_w) + delta_S' * delta_S ./ (delta_S * delta_w);    [x,fval,exitflag,output,grad,W] = W_w_lambda_Gini(N, aimFair, mean, sigma, lambda);        endop_th = -T;op_fair = F + aimFair;op_w = w;