dvtsp_ga_basic :Truck, Multi-drone Evolutionary Routing Prob

Evolutionary Genetic Algorithm to ~optimally route the Truck-Multiple Drone Configuration

FUNCTION: dvtsp_ga_basic calculates the minimum delivery time for a truck and
% multiple (nu) drones to deliver n parcels where each drone is capable of
% working in tandem with the truck to deliver only one parcel.
% System parameters for the drones are:
% kappa = drone range,
% alpha = drone speed as a factor of truck speed (1)
% nu = number of drones assigned to assist the truck.
% Given a graph G(V,E) with vertices V and edges E, the algorithm routes
% the truck ~optimally by assigning drones while routing the truck.
% For any operation (launch, delivery, rendezvous), one or up to nu drones
% may be assigned deliveries within range such that they can rendezvous
% back with the truck at the truck's next delivery location.

% Inputs:
% population size
% number of iterations
% xy coordinates
% alpha: max speed of drone as a factor of truck speed
% kappa: max range of drone (i.e. km)
% nu: max number of drones assigned to a truck
% Outputs:
% minimum ~optimal time based on distance with speed=1
% truck route
% drone route
%
% Evolutionary Algorithm (EA) uses uses a tournament mutation approach.

% Example of inputs:
% nStops = 20; % Number of delivery stops for truck-and-drones
% popSize = 500; % Size of the population of trials for mutation.
% numIter = 3500; % Number of iterations of GA; iteration budget.
% alpha = 2; % Speed of drone as a factor of truck
% kappa = 10; % Range of drone (i.e. 10 km)
% nu = 4; % Max number of drones assigned to truck
% xy = 50*rand([nStops,2]); % coordinates of stops