遗传算法求最短路径的matlab程序,

遗传算法求最短路径的matlab程序,
遗传算法求最短路径的matlab程序,

遗传算法求最短路径的matlab程序,
function [path, totalCost, farthestPreviousHop, farthestNextHop] = dijkstra(n, netCostMatrix, s, d, farthestPreviousHop, farthestNextHop)
% path: the list of nodes in the path from source to destination;
% totalCost: the total cost of the path;
% farthestNode: the farthest node to reach for each node after performing
% the routing;
% n: the number of nodes in the network;
% s: source node index;
% d: destination node index;


% clear;
% noOfNodes = 50;
% rand('state', 0);
% figure(1);
% clf;
% hold on;
% L = 1000;
% R = 200; % maximum range;
% netXloc = rand(1,noOfNodes)*L;
% netYloc = rand(1,noOfNodes)*L;
% for i = 1:noOfNodes
% plot(netXloc(i), netYloc(i), '.');
% text(netXloc(i), netYloc(i), num2str(i));
% for j = 1:noOfNodes
% distance = sqrt((netXloc(i) - netXloc(j))^2 + (netYloc(i) - netYloc(j))^2);
% if distance = R
% matrix(i, j) = 1; % there is a link;
% line([netXloc(i) netXloc(j)], [netYloc(i) netYloc(j)], 'LineStyle', ':');
% else
% matrix(i, j) = inf;
% end;
% end;
% end;
%
%
% activeNodes = [];
% for i = 1:noOfNodes,
% % initialize the farthest node to be itself;
% farthestPreviousHop(i) = i; % used to compute the RTS/CTS range;
% farthestNextHop(i) = i;
% end;
%
% [path, totalCost, farthestPreviousHop, farthestNextHop] = dijkstra(noOfNodes, matrix, 1, 15, farthestPreviousHop, farthestNextHop);
% path
% totalCost
% if length(path) ~= 0
% for i = 1:(length(path)-1)
% line([netXloc(path(i)) netXloc(path(i+1))], [netYloc(path(i)) netYloc(path(i+1))], 'Color','r','LineWidth', 0.50, 'LineStyle', '-.');
% end;
% end;
% hold off;
% return;




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% all the nodes are un-visited;
visited(1:n) = 0;

distance(1:n) = inf; % it stores the shortest distance between each node and the source node;
parent(1:n) = 0;

distance(s) = 0;
for i = 1:(n-1),
temp = [];
for h = 1:n,
if visited(h) == 0 % in the tree;
temp=[temp distance(h)];
else
temp=[temp inf];
end
end;
[t, u] = min(temp); % it starts from node with the shortest distance to the source;
visited(u) = 1; % mark it as visited;
for v = 1:n, % for each neighbors of node u;
if ( ( netCostMatrix(u, v) + distance(u)) distance(v) )
distance(v) = distance(u) + netCostMatrix(u, v); % update the shortest distance when a shorter path is found;
parent(v) = u; % update its parent;
end;
end;
end;

path = [];
if parent(d) ~= 0 % if there is a path!
t = d;
path = [d];
while t ~= s
p = parent(t);
path = [p path];

if netCostMatrix(t, farthestPreviousHop(t)) netCostMatrix(t, p)
farthestPreviousHop(t) = p;
end;
if netCostMatrix(p, farthestNextHop(p)) netCostMatrix(p, t)
farthestNextHop(p) = t;
end;

t = p;
end;
end;

totalCost = distance(d);

return;