Code reproducing the numerical simulations of the paper "Optimization Methods for a Shuttle Bus Routing Problem arising in Urban Mobility"
Requires the installation of the Gurobi Optimizer along with Matlab
To change scenario, open stubFunction.m and go to line 28. Then pass parameters on your choice to inhomogeneous_poisson_generation(). E.g.:
% Scenario a (default setting): radius = 10000; % Legnaro = centr [vx,vy] = voronoi(stops_xy(:,1),stops_xy(:,2)); lambda = lambda_values(lv)*Q / (pi*radius^2); M = 5; [xx,yy] = inhomogeneous_poisson_generation(radius,-0.8771*1e4,-0.1668*1e4,lambda,M); % Legnaro = centr
% Scenario b: radius = 10000; % Padua station = decentr [vx,vy] = voronoi(stops_xy(:,1),stops_xy(:,2)); lambda = lambda_values(lv)*Q / (pi*radius^2); M = 3; [xx,yy] = disomogeneous_poisson_generation(radius,-1.5162*1e4,0.6144*1e4,lambda,M); % Padua station = decentr
In addition, parameter beta can be modified at line 85 of stubFunction.m (default: beta = 1)
Finally, in MAIN.m, simulations paramters can be tuned at line 86. The same file is used to run Monte Carlo simulations.