Developing an Advanced Cloud-Based Vehicle Routing and Scheduling System for Urban Freight Transportation

Abstract

In today's challenging sector of logistics and transportation, companies, seek to adapt software which leads to efficient solutions at an acceptable cost. Conventional routing software is developed to solve vehicle routing problem and help managers and planners in decision making. Simultaneously, specific constraints and different VRP (Vehicle Routing Problem) variants are considered each time, such as the Capacitated, the Multi Depot and the Pickup and Delivery VRP. However, the last few years the need for more reliable deliveries and better customer services arose. In addition, reducing travel distance, travel cost and environmental impact are important factors encountered in urban freight transportation. Therefore, routing software needs to take into account multiple constraints. Such constraints are traffic congestion, speed limits, transportation regulations and restricted zones. These constraints affect mainly Time dependent VRP, VRP with Time Windows, Dynamic VRP and Green VRP. Data collection and processing are essential in routing software for solving these variants and offering the best solution. The methods for solving these problems, along with technological achievements, including cloud computing, can lead to efficient, easily adaptable routing software. Such software solutions can eventually render companies with complex transportation and logistics problems, competitive. The scope of this paper is to describe the concept and methodological approach for the development of such a routing and scheduling system, operating in a cloud environment. The definition of its requirements and the development of the system is the main purpose of an ongoing research project, being in its first stages of system's analysis and design.

Heuristic Algorithms for Co-scheduling of Edge Analytics and Routes for UAV Fleet Missions

“…VRP is a variant of TSP with multiple salespersons [14] and it is NP-hard [18]. This problem has had several extensions to handle realistic scenarios, such as temporal constraints that impose deliveries only at specific time-windows [19], capacity constraints on vehicle payloads [20], multiple trips for vehicles [21], profit per vehicle [22] and traffic congestion [23]. VRP has also been adapted for route planning for a fleet of ships [24], and for drone assisted delivery of goods [25].…”

Green Paradox in Emerging Tourism Supply Chains: Achieving Green Consumption Behavior through Strategic Green Marketing Orientation, Brand Social Responsibility, and Green Image

“…In this situation, routing software may deal with the problem but it may also face some constraints that include traffic congestion, vehicle speed limits, transportation regulations, and restricted zones. Further, these constraints affect time-dependent vehicle-routing problems (VRP), VRP with time windows, dynamic VRP, and green VRP [21,22]. To reduce the environmental and social impact, the proper use of traffic congestion information can significantly improve public confidence in reduced traffic and confidence in the road network [23].…”

Leaders’ Perspectives on IoT Security Risk Management Strategies in Surveyed Organizations Relative to IoTSRM2

“…With respect to the various application areas of IoT, examples of studies include the comprehensive review conducted by Khanna and Kaur [6] that highlighted, among others, various contributions of researchers in different areas of applications of IoT, and the comprehensive literature-based survey conducted by Hassan et al [7] that focused on exploring the applications of IoT in different areas, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. Then, with respect to the individual application areas of IoT, examples of studies include the research works about an advanced IoT-based transportation system for efficient vehicle routing and scheduling in urban areas that described the concept and methodological approach for its development [8], proposed its architecture [9], and demonstrated its use in a case study [10]. Thus, the various application areas of IoT along with the numerous research contributions in different areas of applications of IoT indicate an extensive appetite for leveraging IoT technologies.…”