| Vehicle fleet planning is responsible for a significant proportion of economical, social, and environmental aspects of modern transportation systems. In this thesis, two prevailing planning issues are the main focus, namely, the routing of capacitated vehicles to visit all customers, and the scheduling of service to meet timing or precedence restrictions imposed on vehicle routes. In many applications where these issues appear, the problems can be formulated as the Vehicle Routing Problem with Time Windows (VRPTW). These applications encompass diverse activities such as retail distribution, school bus routing, mail and newspaper delivery, municipal waste collection, fuel and oil delivery, e-commerce, etc. The problem is typically focused on the efficient use of a fleet of capacitated vehicles that must make a number of stops to serve a set of customers so as to minimize cost, subject to vehicle capacity constraint and service time restrictions imposed at the customer locations. Due to the complexity of the problem, metaheuristics are often used for analyzing and solving practical sized instances.; Recognizing the complexity and the wide applicability, this thesis addresses the VRPTW by developing Ant Colony System based approaches for solving it. Pheromone update strategies with the concept of parallel processing have been developed to come up with an approach that can solve the problem more efficiently. The main concern here is to find a useful mechanism for sharing pheromone information and to organize the interaction among cooperating colonies in a more manageable control structure. |
