Project: Report added

Project/scripts/minimizeConstV.m

@@ -20,25 +20,29 @@ normalizeSum  = @(x, S) (x ./ sum(x)) * S;     % Ensure sum of single row x equa
 normalizeSum2 = @(x, S) (x ./ sum(x, 2)) * S;  % Ensure sum of each row of 2D matrix x equals S
 
 % Genetic Algorithm Parameters
-popSize = 100;       % Population size
+popSize = 36;       % Population size
 maxGen = 2000;       % Maximum number of generations
-mutationRate = 0.05; % Mutation probability
+mutationRate = 0.1; % Mutation probability
 
 % Initialize Population
 pop = rand(popSize, N) .* c;    % Random initial solutions (0 <= x <= c)
 pop = normalizeSum2(pop, V);    % Ensure sum of each solution equals V
 
 newPop = zeros(popSize, N);     % Pre-allocate new population buffer
+bestFitness = zeros(maxGen, 1); % Result array
 
 % Genetic Algorithm Execution
 for gen = 1:maxGen
     % Fitness Calculation
     fitness = arrayfun(@(i) fitnessFunction(pop(i, :), t, a, c, V, travelTime), 1:popSize);
-    
+
     % Selection
     [~, idx] = sort(fitness); % Sort based on fitness (ascending order)
     pop = pop(idx, :);        % Retain the best solutions
     
+    % Keep the best chromosome
+    bestFitness(gen) = fitnessFunction(pop(1, :), t, a, c, V, travelTime);
+
     % Crossover
     newPop(1:popSize/2, :) = pop(1:popSize/2, :); % Retain top half
     for i = 1:popSize/2
@@ -63,14 +67,24 @@ for gen = 1:maxGen
     pop = newPop;
 end
 
-% Final Solution
-bestSolution = pop(1, :);
-bestFitness = fitnessFunction(bestSolution, t, a, c, V, travelTime);
-
 % Results
+bestSolution = pop(1, :);
 disp('Best Solution [veh/min]:');
 disp(bestSolution);
-disp(['Best Objective Value: ', num2str(bestFitness), ' [min]']);
+disp(['Best Objective Value: ', num2str(bestFitness(end)), ' [min]']);
+
+figure('Name', 'Time over generations', 'NumberTitle', 'off');
+set(gcf, 'Position', [100, 100, 960, 640]); % Set the figure size
+plot(1:maxGen, bestFitness, '-b', 'LineWidth', 1);
+
+% Customize the plot
+title(['Population = ', num2str(popSize), '   -   Mutation = ', num2str(mutationRate)], 'Interpreter', 'latex', 'FontSize', 16); % Title of the plot
+xlabel('Generations') ;
+ylabel('T_{total}');
+
+% save the figure
+print(gcf, ['figures/constV_pop_', num2str(popSize), 'mut_', num2str(mutationRate), '.png'], '-dpng', '-r300');
+
 
 % Fitness Function
 function T_total = fitnessFunction(x, t, a, c, V, travelTime)