Congestion avoidance: optimization of vehicle routing planning for the logistics industry

This research focuses on the development of ecient solution methods to solve time dependent orienteering problems (TD-OP) in real time. Orienteering problems are used in logistic and touristic cases were an optimal combination of locations needs to be selected and the routing between the locations needs to be optimized. In the time dependent variant the travel time between two locations depends on the departure time at the rst location

Un modelo para resolver el problema dinámico de despacho de vehículos con incertidumbre de clientes y con tiempos de viaje en arcos

Indexación: Web of Science; ScieloIn a real world case scenario, customer demands are requested at any time of the day requiring services that are not known in advance such as delivery or repairing equipment. This is called Dynamic Vehicle Routing (DVR) with customer uncertainty environment. The link travel time for the roadway network varies with time as traffic fluctuates adding an additional component to the dynamic environment. This paper presents a model for solving the DVR problem while combining these two dynamic aspects (customer uncertainty and link travel time). The proposed model employs Greedy, Insertion, and Ant Colony Optimization algorithms. The Greedy algorithm is utilized for constructing new routes with existing customers, and the remaining two algorithms are employed for rerouting as new customer demands appear. A real world application is presented to simulate vehicle routing in a dynamic environment for the city of Taipei, Taiwan. The simulation shows that the model can successfully plan vehicle routes to satisfy all customer demands and help managers in the decision making process.En un escenario real, los pedidos de los clientes son solicitados a cualquier hora del día requiriendo servicios que no han sido planificados con antelación tales como los despachos o la reparación de equipos. Esto es llamado ruteo dinámico de vehículos (RDV) considerando un ambiente con incertidumbre de clientes. El tiempo de viaje en una red vial varía con el tiempo a medida que el tráfico vehicular fluctúa agregando una componente adicional al ambiente dinámico. Este artículo propone un modelo para resolver el problema RDV combinando estos dos aspectos dinámicos. El modelo propuesto utiliza los algoritmos Greedy, Inserción y optimización basada en colonias de hormigas. El algoritmo Greedy es utilizado para construir nuevas rutas con los clientes existentes y los otros dos algoritmos son usados para rutear vehículos a medida que surjan nuevos clientes con sus respectivos pedidos. Además, se presenta una aplicación real para simular el ruteo vehicular en un ambiente dinámico para la ciudad de Taipei, Taiwán. Esta simulación muestra que el modelo es capaz de planificar exitosamente las rutas vehiculares satisfaciendo los pedidos de los clientes y de ayudar los gerentes en el proceso de toma de decisiones.http://ref.scielo.org/3ryfh

Vehicle routing under time-dependent travel times: the impact of congestion avoidance

Daily traffic congestions form major problems for businesses such\ud as logistical service providers and distribution firms. They cause\ud late arrivals at customers and additional hiring costs for the truck\ud drivers. The additional costs of traffic congestions can be reduced\ud by taking into account and avoid well-predictable traffic congestions\ud within off-line vehicle route plans. In the literature, various strategies\ud are proposed to avoid traffic congestions, such as selecting alternative routes, changing the customer visit sequences, and changing the\ud vehicle-customer assignments. We investigate the impact of these and\ud other congestion avoidance strategies in off-line vehicle route plans on\ud the performance of these plans in reality. For this purpose, we develop\ud a set of VRP instances on real road networks, and a speed model that\ud inhabits the main characteristics of peak hour congestion. The instances are solved for different levels of congestion avoidance using a\ud modified Dijkstra algorithm and a restricted dynamic programming\ud heuristic. Computational experiments show that 99% of late arrivals\ud at customers can be eliminated if traffic congestions are accounted for\ud off-line. On top of that, almost 70% of the extra duty times caused by\ud the traffic congestions can be eliminated by clever avoidance strategies

Data allocation and application for time-dependent vehicle routing in city logistics

In city logistics, service providers have to consider dynamics within logistics processes in order to achieve higher schedule reliability and delivery flexibility. To this end, city logistics routing demands for time-dependent travel time estimates and time-dependent optimization models. We consider the process of allocation and application of empirical traffic data for time-dependent vehicle routing in city logistics with respect to its usage. Telematics based traffic data collection and the conversion from raw empirical traffic data into information models are discussed. A city logistics scenario points out the applicability of the information models provided, which are based on huge amounts of real traffic data (FCD). Thus, the benefits of time-dependent planning in contrast to common static planning methods can be demonstrated

AGILE SOLUTIONS & DATA ANALITICS FOR LOGISTICS PROVIDERS BASED ON SIMULATION

The current advances are enabling the development of new solutions in data analytics and decision making in many fields; it is quite interesting to analyze the impact of this approach on logistics providers; this paper proposes examples of these challenges in this context as well as an example of a simulation based solution able to interconnect the different information sources and to fuse the data in order to analyze the logistics processes and support decisions. The proposed solution is based on web services and web application that are adopting the MSaaS concept (Modeling & Simulation as a Service) by using stochastic models

Goal Programming Approach for Carrying People with Physical Disabilities

Most of today\u27s optimization efforts aim to reduce costs, time or the number of resources used. However, optimization efforts should consider other factors as important as these, such as facilitating the lives of the disabled, elderly and pregnant and helping them in their daily lives. In this study, the Nuh Naci Yazgan (NNY) University (Kayseri/Turkey) personnel transport problems were discussed. The NNY University provides a shuttle service to bring employees to school at the start of the work and to leave them at home after work. In order to shorten the collection / distribution time and the total distance travelled, the service vehicle does not leave / pick up all employees in front of their homes. Instead, the employees are picked up / dropped at appropriate locations on an intuitively determined route. Since only the time and cost savings are taken into account when determining the service route, some employees have a long walking distance to the service route. This creates a very important problem, especially for the disabled and pregnant workers. In this study, a new mathematical model is proposed which takes into consideration the physical disadvantages and occupational positions of the employees in order to determine the shortest vehicle route. The results show that the proposed model can significantly reduce walking distances of physically disabled people without compromising the total distance travelled by the vehicle.</p