Vehicle Routing Problems with Time Windows Using Simulated Annealing

Supply chain management is paid attention to every large enterprise. Enterprise reduces their transporting and distributing cost through the manner of subcontractors and shared transportation. The customer request for sending time of the goods is getting more strictly; it can be solved in the vehicle routing problem with time windows (VRPTW). Because the constraints of VRPTW include the length of each route, loading capacity of vehicle and the available time window for each customer, it is more complex than travel salesperson problem and vehicle routing problem (VRP). This research applied the simulated annealing (SA) combined with local search for solving the VRPTW. The developed approach can escape from the local optimal traps, and the use of exchange and insertion local search can find out the (near) optimal solution quickly and efficiently. The Solomon's benchmark instances are used for verifying the developed approach. All problems have 100 customers, a delivery depot, constraints of loading capacity and time window. The developed approach finds all the best results in the C set, and find out 4 solutions which are equal to the best solutions found so far in R set and RC set at reasonable computational time. The developed approach finds the average number of vehicles and route costs in most classes are better than or equal to those of previous researches. Therefore, the developed approach can be used to solve the VRPTW effectively.