Dynamic vehicle routing for solid waste management

This work focuses on the changing demands which is contributed to dynamism and complexity of the routing problems. Most of vehicle routing problems (VRP) have been characterized by static and deterministic problem. To fill the gap, the present study aims at obtaining a set of routes that minimize the total expected routing risk in a dynamic vehicle routing problem (DVRP). Here, for clustering the customers Modified Capacitated K-Means algorithm (M-KMA) is used and Variable Neighbourhood Search algorithm (VNS) for optimizing the obtained routes. For each of the dynamic request of customers the clustering algorithm reschedule the obtained routes and thereby managing the solid waste pickup effectively.