Algorithm for the Time-dependent Dynamic Vehicle Routing Problem with Time-windows

It is well known that the final cost of commercial products is mostly due to expenses than to their transport. In this context, the vehicle routing problem appears aiming to optimize the routes of a fleet which is responsible for providing pick-up and delivery services. In face of the necessity in attending requests that come during the fleet operation time, the dynamic vehicle routing problem appears. This paper brings an approach to obtain good quality solutions to the time-dependent dynamic time-window vehicle routing problem. A framework was proposed based on generation column heuristic that uses an evolutionary algorithm aiming to generate a solution set to the problem. This algorithm was associated to the set partitioning problem mathematic formulation, which aims to obtain the best route combination that attends to the problem constraints, using the routes found by evolutionary algorithm. Three dynamic policies were presented to determine the moment at which the new requests are sent to the dynamic evolucionary algorithm. The Online policy sends the request as soon as it is generated. The Size Demand policy stores the new requests in a buffer and sends them forward to the dynamic evolucionary algorithm only when the buffer is full. While the Periodic policy waits for a fixed period of time before sending forward a new request to the dynamic evolutionary algorithm. The framework was tested with the classic instances proposed by Solomon1987). Tests were performed using the three policies presented and the results were analyzed by statistics.