Towards a Testbed for Dynamic Vehicle Routing Algorithms

Since modern transport services are becoming more flexible, demand-responsive, and energy/cost efficient, there is a growing demand for large-scale microscopic simulation platforms in order to test sophisticated routing algorithms. Such platforms have to simulate in detail, not only the dynamically changing demand and supply of the relevant service, but also traffic flow and other relevant transport services. This paper presents the DVRP extension to the open-source MATSim simulator. The extension is designed to be highly general and customizable to simulate a wide range of dynamic rich vehicle routing problems. The extension allows plugging in of various algorithms that are responsible for continuous re-optimisation of routes in response to changes in the system. The DVRP extension has been used in many research and commercial projects dealing with simulation of electric and autonomous taxis, demand-responsive transport, personal rapid transport, free-floating car sharing and parking search

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

Tackling Dynamic Vehicle Routing Problem with Time Windows by means of Ant Colony System

The Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) is an extension of the well-known Vehicle Routing Problem (VRP), which takes into account the dynamic nature of the problem. This aspect requires the vehicle routes to be updated in an ongoing manner as new customer requests arrive in the system and must be incorporated into an evolving schedule during the working day. Besides the vehicle capacity constraint involved in the classical VRP, DVRPTW considers in addition time windows, which are able to better capture real-world situations. Despite this, so far, few studies have focused on tackling this problem of greater practical importance. To this end, this study devises for the resolution of DVRPTW, an ant colony optimization based algorithm, which resorts to a joint solution construction mechanism, able to construct in parallel the vehicle routes. This method is coupled with a local search procedure, aimed to further improve the solutions built by ants, and with an insertion heuristics, which tries to reduce the number of vehicles used to service the available customers. The experiments indicate that the proposed algorithm is competitive and effective, and on DVRPTW instances with a higher dynamicity level, it is able to yield better results compared to existing ant-based approaches.Comment: 10 pages, 2 figure

An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols

Coercion resistance is an important and one of the most intricate security requirements of electronic voting protocols. Several definitions of coercion resistance have been proposed in the literature, including definitions based on symbolic models. However, existing definitions in such models are rather restricted in their scope and quite complex. In this paper, we therefore propose a new definition of coercion resistance in a symbolic setting, based on an epistemic approach. Our definition is relatively simple and intuitive. It allows for a fine-grained formulation of coercion resistance and can be stated independently of a specific, symbolic protocol and adversary model. As a proof of concept, we apply our definition to three voting protocols. In particular, we carry out the first rigorous analysis of the recently proposed Civitas system. We precisely identify those conditions under which this system guarantees coercion resistance or fails to be coercion resistant. We also analyze protocols proposed by Lee et al. and Okamoto.Comment: An extended version of a paper from IEEE Symposium on Security and Privacy (S&P) 200

The Influence of Multi-agent Cooperation on the Efficiency of Taxi Dispatching

The paper deals with the problem of the optimal collaboration scheme in taxi dispatching between customers, taxi drivers and the dispatcher. The authors propose three strategies that differ by the amount of information exchanged between agents and the intensity of cooperation between taxi drivers and the dispatcher. The strategies are evaluated by means of a microscopic multi-agent transport simulator (MATSim) coupled with a dynamic vehicle routing optimizer (DVRP Optimizer), which allows to realistically simulate dynamic taxi services as one of several different transport means, all embedded into a realistic environment. The evaluation is carried out on a scenario of the Polish city of Mielec. The results obtained prove that the cooperation between the dispatcher and taxi drivers is of the utmost importance, while the customer–dispatcher communication may be reduced to minimum and compensated by the use of more sophisticated dispatching strategies, thereby not affecting the quality of service

Analysis of the characteristics and applications associated to the dynamic vehicle routing problem - DVRP

El Problema del Ruteo Dinámico de Vehículos - DVRP, permite analizar sistemas con la inclusión de una variable de carácter dinámico, ajustando el ruteo en función de nuevas restricciones y comportamientos a nivel de desarrollo de dimensiones temporales y desarrollo constructivo con información en tiempo real. Este problema se ha clasificado en diferentes sistemas, de acuerdo a su aplicabilidad y algoritmos de solución, además del efecto del dinamismo presente. Sin embargo, no todas las características y diferencias frente al ruteo estocástico clásico, han sido mencionadas y resaltadas, debido a su reciente desarrollo, así como la limitada investigación desarrollada. Por tal motivo el presente artículo, plantea la realización de un análisis de las principales características y aplicaciones asociadas a los problemas de ruteo dinámico de vehículos., a través de una revisión bibliográfica con el propósito de brindar información acerca de las características principales, fortalezas respecto al problema clásico y sus aplicaciones para solución. La metodología empleada, incluye una investigación cualitativa, basada en la búsqueda sistemática en bases de datos acerca del DVRP, en últimos cuatro años (2011-2014). Se concluye que el problema de ruteo dinámico de vehículos, permite establecer y analizar sistemas de ruteo, con la inclusión de una variable de carácter dinámico, permitiendo la aplicación y ajuste de heurísticas y metaheurísticas, permitiendo abarcar nuevos sistemas de análisis a nivel logístico. De la misma manera se evidencia que existe un comportamiento variable con tendencia a la baja, en referencia al número de publicaciones relacionadas con el tema, reflejando, un potencial de investigación y desarrollo inexplorado en referencia a la aplicación y ajuste de la temáticaThe Dynamic Vehicle Routing Problem- DVRP allows analyzing systems with the inclusion of a dynamic variable, adjusting the routing in function of new restrictions and behaviors at the development level of temporal dimensions and constructive development with real-time information. This problem has been classified into different systems, according to their applicability and solution algorithms, besides the current dynamic effect. However, not all features and differences compared to classical stochastic routing have been mentioned and highlighted because of their recent development, as well as limited research developed. Therefore, the present article proposes to carry out an analysis about the main features and applications associated with the dynamic routing vehicle problem, through a literature review with the purpose of providing information about the main characteristics, strengths compared to the classical problem and its applications to solution. The methodology includes a qualitative research based on a systematic search in databases about DVRP in last four years (2011-2014). As main conclusion, is related that the DVRP allows establishing and analyzing routing systems, with the inclusion of a variable dynamic, allowing the application and set of heuristics and metaheuristics, allowing embrace new analysis systems in a logistical level. Likewise, it is evident that there is a variable behavior downtrend, referring to the number of publications related to the theme, reflecting unexplored potential in research and development in reference to the application and setting the them

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Towards Multi-Agent Simulation of the Dynamic Vehicle Routing Problem in MATSim

The paper presents the idea and the initial outcomes of integrating MATSim, a multi-agent transport simulation system, with the DVRP Optimizer, an application for solving the Dynamic Vehicle Routing Problem. First, the justification for the research is given and the state of the art is outlined. Then, MATSim is presented with a short description of the recent results in areas related to the one proposed in the paper, followed up by the discussion on the DVRP Optimizer functionality, architecture and implemented algorithms. Next, the process of integrating MATSim and the DVRP Optimizer is presented, with the distinction of two phases, the off-line and on-line optimization. Then, a description of the off-line optimization is given along with the results obtained for courier and taxi services in urban areas. The paper ends with conclusions and future plans

Look-ahead strategies for dynamic pickup and delivery problems

In this paper we consider a dynamic full truckload pickup and delivery problem with time-windows. Jobs arrive over time and are offered in a second-price auction. Individual vehicles bid on these jobs and maintain a schedule of the jobs they have won. We propose a pricing and scheduling strategy based on dynamic programming where not only the direct costs of a job insertion are taken into account, but also the impact on future opportunities. Simulation is used to evaluate the benefits of pricing opportunities compared to simple pricing strategies in various market settings. Numerical results show that the proposed approach provides high quality solutions, in terms of profits, capacity utilization, and delivery reliability