Input: Distance matrix D, Initial temperature , Cooling rate , Maximum iteration Maxit Output: Best Solution 1: Generate n feasible routes randomly, , compute the Euclidean distance/fitness value of each route, , assign the value of Maxit and the initial value of and 2: For each iteration, it = 1 to maximum iteration 3: For each route , to n 4: Generate a new route by adopting neighborhood structure (described in Section 3.2.1) 5: Compute Euclidean distance/fitness value of the new route 6: Calculate on the basis of Equation (11) 7: If , then update the current route by assigning 8: If , then compute the acceptance probability p by using Equation (10). If , then update the current route by assigning , where u is the random number between 0 and 1 9: End for 10: Decrease the temperature based on Equation (12) 11: Update the best solution ever found 12: End for |