(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 9, 2017 306 | Page www.ijacsa.thesai.org Distributed Swarm Optimization Modeling for Waste Collection Vehicle Routing Problem ELGAREJ Mouhcine, MANSOURI Khalifa, YOUSSFI Mohamed, BENMOUSSA Nezha, EL FAZAZI Hanae Laboratory SSDIA, ENSET University Hassan II Mohammedia, Morocco Abstract—In this paper, we consider a complex garbage collection problem, where the residents of a particular area dispose of recyclable garbage, which is collected and managed using a fleet of trucks with different weight capacities and volume. This tour is characterized by a set of constraints such as the maximum tour duration (in term of distance and the timing) consumed to collect wastes from several locations. This problem is modeled as a garbage collection vehicle routing problem, which aims to minimize the cost of traveling routes (minimizing the distance traveled) by finding optimal routes for vehicles such that all waste bins are emptied and the waste is driven towards the disposal locations. We propose a distributed technique based on the Ant Colony system Algorithm to find optimal routes that help vehicles to visit all the wastes bins using interactive agents consumed based on the behavior of real ants. The designed solution will try to create a set of layers to control and manage the waste collection, each layer will be handled by an intelligent agent which is characterized by a specific behavior, in this architecture a set of behaviors have been designed to optimizing routes and control the real time capacity of vehicles. Finally, manage the traffic messages between the different agents to select the best solutions that will be assigned to each vehicle. The developed solution performs well compared to the traditional solution on small cases. Keywords—Vehicle routing system; ant colony optimization; multi-agent system; garbage collection system I. INTRODUCTION The vehicle routing problem [1]-[3] includes the optimization of a set of minimum cost transportation routes to serve a various set of customers using a dynamic or a fixed fleet of transportation trucks (vehicles, trucks …). The map of this problem contains a set of routes associated with several points or locations named as depots. Each customer is visited by only one vehicle. The vehicle must follow the optimal route proposed by the system. This problem combines several types of constraints, such as the limit of the total distance covered by each vehicle and total working time per day, the availability of resources (vehicles, customers’ data, salesman …). There are many different models of vehicle routing problem. We consider in this paper a waste collection problem [4]-[8] where a number of vehicles are used for collecting waste from different households (clients). Those wastes must be collected from several areas and take them back toward the disposal facilities locations. Each vehicle is characterized by its capacity and the number of waste locations to visit. At the beginning, all available vehicles are assigned to the depot (Fig. 1). Each vehicle will start its cycle to collect wastes from the different locations according to the path planning proposed by the central unit. Wastes are collected until the capacity of the vehicle is reached. Then it disposes the waste to a disposal facility predefined and repeats the same process during its working time. At the end, all the vehicles must return to the depot. Fig. 1. The garbage collection management. In the classical garbage collection method, the system is based on a successive process, it means that when a vehicle is not able to accomplish his task we cannot use another vehicle to terminate the unfinished tasks, this happens when a vehicle exceeds his capacity limit. In the other hand, if we increase the number of available vehicles to avoid the capacity limit and to reach all the wastes points, it may produce that vehicles will use only the three quarters of their capacity for collecting all wastes from the different locations. Actually, with the new intelligent systems, we can create a new distributed mechanism to control the map of the waste locations and the disposal facilities to built a new path planning for each vehicle based on real time data sent by the vehicle which contains his actual position and his capacity. According to this information, the system will be able to assign the best circuit to the nearest vehicle. Actually, we can use a set of embedded systems [12], [14] for collecting all helpful data such as the actual capacity of each vehicle at each location, also, notifying each vehicle by the new path planning created when one of the available vehicles arrive at his capacity limit. We can say that our problem is based on dynamic data, so, the system should be able to receive the new information and re-used to re- calculated the new alternative paths planning for each working vehicle.