bonjour ,j'ai trouvé ce code en Matlab mais malheureusement je n'ai pas étudié sur ce langage,je ne le connais pas ,je n'arrive pas à le traduir en C,svp j'ai besoin d'aide
MATLAB Code for Tabu Search
% Travelling Sales man problem using Tabu Search
% This assumes the distance matrix is symmetric
% Tour always starts from node 1
% **********Read distance (cost) matrix from Excel sheet "data.xls"******
d = xlsread('input_data127.xls');
d_orig = d;
start_time = cputime;
dim1 = size(d,1);
dim12 = size(d);
for i=1:dim1
d(i,i)=10e+06;
end
% *****************Initialise all parameters**********************
d1=d;
tour = zeros(dim12);
cost = 0;
min_dist=[ ];
short_path=[ ];
best_nbr_cost = 0;
best_nbr = [ ];
% *******Generate Initial solution - find shortest path from each node****
% if node pair 1-2 is selected, make distance from 2 to each of earlier
%visited nodes very high to avoid a subtour
k = 1;
for i=1:dim1-1
min_dist(i) = min(d1(k,:));
short_path(i) = find((d1(k,:)==min_dist(i)),1);
cost = cost+min_dist(i);
k = short_path(i);
% prohibit all paths from current visited node to all earlier visited nodes
d1(k,1)=10e+06;
for visited_node = 1:length(short_path); 6
d1(k,short_path(visited_node))=10e+06;
end
end
tour(1,short_path(1))=1;
for i=2:dim1-1
tour(short_path(i-1),short_path(i))=1;
end
%Last visited node is k;
%shortest path from last visited node is always 1, where the tour
%originally started from
last_indx = length(short_path)+1;
short_path(last_indx)=1;
tour(k,short_path(last_indx))=1;
cost = cost+d(k,1);
% A tour is represented as a sequence of nodes startig from second node (as
% node 1 is always fixed to be 1
crnt_tour = short_path;
best_tour = short_path;
best_obj =cost;
crnt_tour_cost = cost;
fprintf('\nInitial solution\n');
crnt_tour
fprintf('\nInitial tour cost = %d\t', crnt_tour_cost);
nbr_cost=[ ];
% Initialize Tabu List "tabu_tenure" giving the number of iterations for
% which a particular pair of nodes are forbidden from exchange
tabu_tenure = zeros(dim12);
max_tabu_tenure = round(sqrt(dim1));
%max_tabu_tenure = dim1;
penalty = zeros(1,(dim1-1)*(dim1-2)/2);
frequency = zeros(dim12);
frequency(1,:)=100000;
frequency(:,1)=100000; 7
for i=1:dim1
frequency(i,i)=100000;
end
iter_snc_last_imprv = 0;
%*********Perform the iteration until one of the criteria is met***********
%1. Max number of iterations reached***************************************
%2. Iterations since last improvement in the best objective found so far
% reaches a threshold******************************************************
best_nbr = crnt_tour;
for iter=1:10000
fprintf('\n*****iteration number = %d*****\n', iter);
nbr =[];
% *******************Find all neighbours to current tour by an exchange
%******************between each pair of nodes***********************
% ****Calculate the object value (cost) for each of the neighbours******
nbr_cost = inf(dim12);
for i=1:dim1-2
for j=i+1:dim1-1
if i==1
if j-i==1
nbr_cost(crnt_tour(i),crnt_tour(j))=crnt_tour_cost-d(1,crnt_tour(i))+d(1,crnt_tour(j))- d(crnt_tour(j),crnt_tour(j+1))+d(crnt_tour(i),crnt_tour(j+1));
best_i=i;
best_j=j;
best_nbr_cost = nbr_cost(crnt_tour(i),crnt_tour(j));
tabu_node1 = crnt_tour(i);
tabu_node2 = crnt_tour(j);
else
nbr_cost(crnt_tour(i),crnt_tour(j))=crnt_tour_cost-d(1,crnt_tour(i))+d(1,crnt_tour(j))- d(crnt_tour(j),crnt_tour(j+1))+d(crnt_tour(i),crnt_tour(j+1))- d(crnt_tour(i),crnt_tour(i+1))+d(crnt_tour(j),crnt_tour(i+1))-d(crnt_tour(j- 1),crnt_tour(j))+d(crnt_tour(j-1),crnt_tour(i));
end
else
if j-i==1
8
nbr_cost(crnt_tour(i),crnt_tour(j))=crnt_tour_cost-d(crnt_tour(i-1),crnt_tour(i))+d(crnt_tour(i- 1),crnt_tour(j))-d(crnt_tour(j),crnt_tour(j+1))+d(crnt_tour(i),crnt_tour(j+1));
else
nbr_cost(crnt_tour(i),crnt_tour(j))=crnt_tour_cost-d(crnt_tour(i-1),crnt_tour(i))+d(crnt_tour(i- 1),crnt_tour(j))-d(crnt_tour(j),crnt_tour(j+1))+d(crnt_tour(i),crnt_tour(j+1))- d(crnt_tour(i),crnt_tour(i+1))+d(crnt_tour(j),crnt_tour(i+1))-d(crnt_tour(j- 1),crnt_tour(j))+d(crnt_tour(j-1),crnt_tour(i));
end
end
if nbr_cost(crnt_tour(i),crnt_tour(j)) < best_nbr_cost
best_nbr_cost = nbr_cost(crnt_tour(i),crnt_tour(j));
best_i=i;
best_j=j;
tabu_node1 = crnt_tour(i);
tabu_node2 = crnt_tour(j);
end
end
end
%*********** Neighbourhood cost calculation ends here***********
best_nbr(best_i) = crnt_tour(best_j);
best_nbr(best_j) = crnt_tour(best_i);
%****Replace current solution by the best neighbour.*******************
%**************Enter it in TABU List ******************
%***Label tabu nodes such that tabu node2 is always greater than tabu
%node1. This is required to keep recency based and frequency based tabu
%list in the same data structure. Recency based list is in the space
%above the main diagonal of the Tabu Tenure matrix and frequency based
%tabu list is in the space below the main diagonal******************
%******Find the best neighbour that does not involve swaps in Tabu List***
%*************** OVERRIDE TABU IF ASPIRATION CRITERIA MET**************
%**************Aspiration criteria is met if a Tabu member is better
%than the best solution found so far**********************************
%while (tabu_tenure(tabu_node1,tabu_node2)|tabu_tenure(tabu_node2,tabu_node1))>0
while (tabu_tenure(tabu_node1,tabu_node2))>0
if best_nbr_cost < best_obj %(TABU solution better than the best found so far) 9
fprintf('\nbest nbr cost = %d\t and best obj = %d\n, hence breaking',best_nbr_cost, best_obj);
break;
else
%***********Make the cost of TABU move prohibitively high to
%***disallow its selection and look for the next best neighbour
%****that is not TABU Active****************************
nbr_cost(tabu_node1,tabu_node2)=nbr_cost(tabu_node1,tabu_node2)*1000;
best_nbr_cost_col = min(nbr_cost);
best_nbr_cost = min(best_nbr_cost_col);
[R,C] = find((nbr_cost==best_nbr_cost),1);
tabu_node1 = R;
tabu_node2 = C;
end
end
%********Continuous diversification when best nbr cost gt crnt*********
%*******tour cost by penalising objective by frequency of moves********
if best_nbr_cost > crnt_tour_cost
fprintf('\nbest neighbor cost greater than current tour cost\n');
min_d_col = min(d);
penal_nbr_cost = nbr_cost + min(min_d_col)*frequency;
penal_best_nbr_cost_col = min(penal_nbr_cost);
penal_best_nbr_cost = min(penal_best_nbr_cost_col);
[Rp,Cp] = find((penal_nbr_cost==penal_best_nbr_cost),1);
tabu_node1 = Rp;
tabu_node2 = Cp;
best_nbr_cost = nbr_cost(tabu_node1,tabu_node2);
end
% *******************Decrease all Tabu Tenures by 1********************
for row = 1:dim1-1
for col = row+1:dim1
if tabu_tenure(row,col)>0
tabu_tenure(row,col)=tabu_tenure(row,col)-1;
tabu_tenure(col,row)=tabu_tenure(row,col);
end
end
10
end
%**********************RECENCY TABU*****************************
%Enter current moves in Tabu List with tenure = maximum tenure**
tabu_tenure(tabu_node1,tabu_node2)=max_tabu_tenure;
tabu_tenure(tabu_node2,tabu_node1)= tabu_tenure(tabu_node1,tabu_node2);
%**********************FREQUENCY TABU*****************************
%Increase the frequency of current moves in Tabu List by 1********
%tabu_tenure(tabu_node2,tabu_node1)=tabu_tenure(tabu_node2,tabu_node1)+1;
frequency(tabu_node1,tabu_node2) = frequency(tabu_node1,tabu_node2)+1;
%********Update current tour**************
crnt_tour=best_nbr;
crnt_tour_cost=best_nbr_cost;
%************Update best tour*******************
if crnt_tour_cost < best_obj
best_obj = crnt_tour_cost;
best_tour = crnt_tour;
iter_snc_last_imprv = 0;
else
iter_snc_last_imprv = iter_snc_last_imprv + 1;
%if iter_snc_last_imprv >= (dim1-1)*(dim1-2)/2
if iter_snc_last_imprv >= 400
fprintf('\n NO improvmennt since last % iterations, hence diversify\n',iter_snc_last_imprv);
min_freq_col = min(frequency); %gives minimum of each column
min_freq = min(min_freq_col);
[R,C] = find((frequency==min_freq),1); %find the moves with lowest frequency
freq_indx1 = R
freq_indx2 = C
indx_in_crnt_tour1 = find(crnt_tour==R); %locate the moves in the crnt tour
indx_in_crnt_tour2 = find(crnt_tour==C);
%Diversify using a move that has the lowest frequency
temp = crnt_tour(indx_in_crnt_tour1);
crnt_tour(indx_in_crnt_tour1) = crnt_tour(indx_in_crnt_tour2);
crnt_tour(indx_in_crnt_tour2) = temp;
tabu_tenure = zeros(dim12);
11
frequency = zeros(dim12);
frequency(1,:)=100000;
frequency(:,1)=100000;
for i=1:dim1
frequency(i,i)=100000;
end
tabu_tenure(R,C)=max_tabu_tenure;
tabu_tenure(C,R)=max_tabu_tenure;
frequency(R,C)=frequency(R,C)+1;
frequency(C,R) = frequency(R,C);
%Re-calculare crnt tour cost
crnt_tour_cost = d(1,crnt_tour(1));
for i=1:dim1-1
crnt_tour_cost = crnt_tour_cost+d(crnt_tour(i),crnt_tour(i+1));
end
iter_snc_last_imprv = 0;
if crnt_tour_cost < best_obj
best_obj = crnt_tour_cost;
best_tour = crnt_tour;
end
end
end
%fprintf('\ncurrent tour\n')
%crnt_tour
fprintf('\ncurrent tour cost = %d\t', crnt_tour_cost);
%fprintf('\nbest tour\n');
%best_tour
fprintf('best obj =%d\t',best_obj);
%pause;
end
fprintf('\nbest tour\n');
best_tour
fprintf('best obj =%d\n',best_obj);
end_time = cputime;
exec_time = end_time - start_time;
fprintf('\ntime taken = %f\t', exec_time);
svp est ce que que vous pouvez m'aider,merci.