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

Dynamic vehicle routing problems: Three decades and counting

Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics.© 2015 Wiley Periodicals, Inc