% Define objective function (minimization) f = [-3; -2]; % Inequality constraints (A*x <= b) A = [2, 1; 1, 1]; b = [10; 8]; % Lower bounds (x >= 0) lb = [0; 0]; % Solve [x, fval] = linprog(f, A, b, [], [], lb); fprintf('Optimal x1: %.2f\n', x(1)); fprintf('Optimal x2: %.2f\n', x(2)); fprintf('Maximized Value: %.2f\n', -fval); Use code with caution. Copied to clipboard 4. Visualization of Constraints
For very large sets of constraints, use sparse matrices for Aeqcap A e q to save memory. Linear Programming Using MATLABВ®
If your variables must be integers, use the intlinprog function instead. % Define objective function (minimization) f = [-3;
You can specify the algorithm using optimoptions . The default is often 'dual-simplex', which is robust for most standard problems. % Solve [x