GIS Based Solution of Multi-Depot Capacitated Vehicle Routing Problem with Time Window Using Tabu Search Algorithm

Population in cities is increasing very rapidly and hence demand of utility commodities is also increasing day by day. There is a need for the fleets of vehicles to deliver goods and material from distribution centres to local consumer locations within optimal travel distance and time. In this study, the above transportation problem have been tackled by solving the vehicle routing problem for the distribution of goods and material from the multiple distribution centres (depots) to the individual customer locations (stores) within predefined time window of each customer and distribution centre, and based on the carrying capacity of the moving vehicle. The Multi-Depot Capacitated Vehicle Routing Problem with Time Window (MDCVRPTW) can be described as the combinatorial optimization transportation problem based on minimum cost route for a fleet of vehicles from the depot to a set of geographically scattered customer locations. The route must be defined in such a way that the each customer location is visited only and only once and only by one vehicle within a given time window, all the routes start and end at the same depot, and the total demand of all the customers on one particular route must not exceed the capacity of the vehicle moving on that route. In this study, geographical information system (GIS) technology is used for obtaining the near optimal solution of MDCVRPTW in terms of minimizing delivery cost with respect to travel distance and travel time, without violating the capacity and total trip time constraints for each vehicle. Multiple parameters like customer demand in terms of type of material and time, service time, waiting time, violation time, vehicle capacity, vehicle type, multiple-distribution centres, trip duration, lunch break during the trip, travel restriction over areas, time window at stores, type of delivered material, time impedance, distance impedance, over time servicing have been considered to perform the MDCVRPTW. We have taken three distribution centres and thirty nine stores, and different types of vehicles like three, four and six wheeler of varying capacity to deliver the goods and materials from the distribution centres to the individual stores. In this study the Tabu search algorithm is used in GIS for the near optimal solution of MDCVRPTW. This algorithm uses three types of movements to obtain multi route adjacent solutions: the relocation, interchange and crossover movements. Computational results are presented and demonstrate the effectiveness of the proposed approach on MDCVRPTW in GIS environment.