Abstract:
The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The vehicle routing problem with simultaneous pickups and deliveries and time windows (VRP-SPDTW) is the problem of optimally integrating forward (good distribution) and reverse logistics (returning materials) for cost saving and environmental protection. This research develops a mathematical optimization model for VRPSDPTW called environmental vehicle routing problem with simultaneous delivery and pickup with time windows (EVRPSDPTW) model by using the traveling distance and the load of vehicle. The aim of this model is to determine the efficient vehicle route of a vehicle under cost optimization including fixed cost, variable cost, penalty cost for being tardy, fuel cost by optimizing fuel consumption and cost of carbon emission which results in reducing energy consumption as well as pollutant emissions in the air (GHG). A hybrid genetic algorithm is presented to address the Vehicle Routing Problem with simultaneous delivery and pickup with Time Window. In order to compare the operational efficiency of HGA, genetic algorithm (GA) is implemented to solve the EVRPSDPTW model. The computational experiment is conducted and the results of computational experiments show the performance of HGA is superior to that of GA in terms of the total cost consumption of a vehicle.
