Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
The vehicle routing problem
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ant based mechanism for crisis response coordination
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
| Hi-index | 0.00 |
The Vehicle Routing Problem with Time Windows (VRPTW) involves scheduling and routing of a vehicle fleet to serve a given set of geographically distributed requests, subject to capacity and time constraints. This problem is encountered in a variety of industrial and service applications, ranging from logistics and transportation systems, to material handling systems in manufacturing. Due to the intrinsic complexity of the problem, heuristics are needed for analyzing and solving it under practical problem sizes. In this paper, a model of an Ant Colony System (ACS) is proposed to solve the VRPTW. The aim here is to investigate and analyze the performance of the foraging model of a single colony ACS to solve the VRPTW from an experimental point of view, with particular emphasis on different initial solution techniques and different visibility (desirability) functions. Finally, experimental analyses are performed to compare the proposed model to other metaheuristic techniques. The results show that the single colony ACS algorithm, despite its simple model, is quite competitive to other well know metaheuristic techniques.