Dynamic Management Of A Delayed Delivery Vehicle In A City Logistics Environment

A review of dynamic vehicle routing problems

“…More specifically, requests can be a demand for goods [2,62,70,71,75,99,101,144] or services [7,11,17,52,89,141]. Travel time, a dynamic component of most real-world applications, has been recently taken into account [1,6,28,48,64,65,94,108,136,139,153]; while service time has not been explicitly studied (but can be added to travel time). Finally, some recent work considers dynamically revealed demands for a set of known customers [104,105,126,128] and vehicle availability [92,93,103], in which case the source of dynamism is the possible breakdown of vehicles.…”

“…They describe the different modules ranging from modeling the city road network and acquiring real-time traffic data to the dynamic routing of a fleet of vehicles. Zeimpekis et al [153] proposed a Decision Support System (DSS) for city logistics which takes into account dynamic travel and service times.…”

Dynamic Coordination in Fleet Management Systems: Toward Smart Cyber Fleets

“…Approaches to fl eet planning typically focus on the development of near-optimal plans using various types of effective vehicle-routing algorithms, which can be either static or dynamic. [2][3][4] Fleet schedules designed a priori with static route planning assume the following: all relevant data is known before the planning starts, short-and longterm decisions have the same importance, and the time available for creation, verification, and implementation of route plans is of minor importance. The use of an initial fl eet schedule, although necessary, is by no means suffi cient because it might not cope adequately with unexpected events during execution, such as traffi c delays, vehicle breakdowns, road works, and new customer requests or the cancellation of preexisting ones, which causes fl eet delays, unexpected costs, and poor customer service.…”

An event-driven optimization framework for dynamic vehicle routing

“…Their DSS includes a real time traffic simulator, connection to common GIS systems, and various routing models and optimization modules. In a different context, Zeimpekis et al [61] developed a DSS that takes into account unexpected events such as traffic conditions or vehicle breakdowns to re-optimize an existing distribution schedule. Li et al [31] also studied vehicle breakdowns in an application to waste collection in Brazil.…”