Diseño de aplicativo de ruteo con inventario entre proveedor y minoristas

En el presente trabajo se muestra el diseño de un aplicativo intuitivo que apoya y complementa la labor de planeación de rutas y manejo de inventarios a través de una heurística que genera soluciones de calidad en tiempos eficientes. El aplicativo se programó en Visual Basic for Applications de Microsoft Excel con una Interfaz de Usuario que recopila información y administran los datos suministrados por la compañía, para que, de forma guiada mediante elementos gráficos desde la introducción del aplicativo, hasta la obtención de resultados se facilite al usuario su uso, la comprensión del desarrollo y las soluciones obtenidas. La heurística funciona mediante tres pilares fundamentales, el primer pilar es la obtención de una solución inicial. Esta solución inicial se genera de forma aleatoria. El segundo pilar, hace referencia a la búsqueda local por medio de la cual se busca mejorar la solución inicial para más adelante ejecutar el tercer pilar que hace referencia a una perturbación o modificación a la solución inicial mejorada dentro del rango de solución factible con el fin de poder explorar y verificar diferentes soluciones y finalmente comparar la solución inicial con la solución de la búsqueda local itera con la solución de la perturbación y seleccionar la mejor de las tres. Al finalizar la comparación, se ejecutan de nuevo secuencialmente cada uno de los tres pilares y se compara con la mejor solución seleccionada, este ciclo se realiza cuantas veces sea necesario hasta encontrar una solución que comparada varias veces siga siendo la mejor.In the present work, it is shown the design of an intuitive application which supports and complements the work of routing planning and inventory management through a metaheuristic that generates quality solutions in efficient times. The application was programmed in Visual Basic for Applications of Microsoft Excel with an user interface where it is collected and administered the data provided by the company that is using it, so that, in a guided by graphics elements from the introduction of the application, until the obtaining of results that facilities the use for the user, the comprehension of the develop and the results. The heuristic works through three fundamental pillars, the first pillar is the obtaining of an initial solution. This initial solution is generated randomly and allow visualize a field of feasible solutions wider. The second pillar, refers to the local search, whereby we want to improve the initial solution for later rum the third pillar that refers to a perturbation or modification of the local search within the range of feasible solution with the purpose of explore and verify different solutions and finally compare the initial solution with the local search with the perturbed solution and select the best of the three. At the end of comparison, it runs again sequentially each of the three pillars and it is comparing with the best solution selected, this cycle is run repeated as many times as necessary until it obtains the best solution of the comparison.Ingeniero (a) IndustrialPregrad

An algorithm based on a granular tabu search for the solution of a vehicle routing problem by considering heterogeneous fleet

This paper considers the vehicle routing problem with heterogeneous fleet (VRPH), which tries to determine the routes to be constructed for satisfying the demand of the customers by considering a fleet of vehicles with different capacities and costs not homogeneous. The main objective is to minimize the distance traversed by the different vehicles. This paper proposes a metaheuristic algorithm based on a granular tabu search for the solution of the problem. The algorithm allows infeasible solutions by penalizing them by a dynamic factor which is adjusted during the search. Computational experiments on real instances for a Colombian company show that the proposed algorithm is able to obtain, within short compu­ting times, better solutions for those obtained by the current traditional method for planning the routes.Este artículo aborda el problema de ruteo de vehículos con flota hetero­génea (VRPH), en el cual se busca determinar las rutas a ser construidas para satisfacer las demandas de los clientes, considerando una flota de vehículos con capacidad y costos no homogéneos. El objetivo es minimi­zar la distancia total de las rutas recorridas por los diferentes vehículos. En este artículo, se propone un algoritmo metaheurístico basado en una búsqueda tabú granular para la solución del problema. El algoritmo acepta soluciones infactibles penalizadas por un factor dinámico que se ajusta durante la búsqueda. Experimentos computacionales en instancias reales de una compañía colombiana muestran que el algoritmo propuesto es capaz de obtener, en tiempos computacionales reducidos, mejores soluciones que las obtenidas por el método tradicional de planificación de rutas, usado en la compañía

A Granular Tabu Search Algorithm for a Real Case Study of a Vehicle Routing Problem with a Heterogeneous Fleet and Time Windows

Purpose: We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW) for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase), a granular tabu search is applied during the improvement phase (second phase). Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.Peer Reviewe

Una aplicación web, para asignación y ruteo de vehículos en caso de desastres

The natural disasters are events that exceed the capacity of covering of a population and generate large losses, both economic and humans, with externalities in many cases not quantified in their entirety. The resources needed to supply the distribution centers are provided both private and government must allocate providers, by the disaster damage. Then, the distribution is performed from the depots, to the different customers or distribution centers. It presents a web application that assigns the super depots, and then establishes the routing that the vehicles must follow to cover the distribution centers, considering different probabilities of populations to be covered. The application is a parametric framework to any geographical area and scenarios, given the existing integration with applications such as Google Maps ®. Computational times are reasonable, and at the software architecture level the product is scalable and extensible. In addition, it complies with a set of good software quality practices present in ISO9126.Los desastres naturales, son eventos que exceden la capacidad de respuesta de una población y generan cuantiosas pérdidas, tanto económicas como humanas, con externalidades en muchos casos no cuantificadas en su totalidad. Los recursos necesarios para abastecer los centros de distribución son provistos tanto por proveedores privados como gubernamentales, deben ser asignados en virtud del daño del desastre. Luego viene la distribución desde los depósitos, hasta los distintos clientes o centros de distribución. Se presenta una aplicación web que asigna los superdepósitos, y luego establece el ruteo que han de seguir los vehículos para cubrir los centros de distribución, considerando diversas probabilidades de poblaciones que han de ser cubiertas. La aplicación es un marco de trabajo paramétrico a cualquier zona geográfica y escenarios, dado la integración existente con aplicaciones como Google Maps ®. Los tiempos computacionales son razonables, a nivel de arquitectura de software el producto es escalable y extensible. Además, cumple con un conjunto de buenas prácticas de calidad de software presentes en la ISO9126

Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems

Researchers who investigate in any area related to computational algorithms (both dening new algorithms or improving existing ones) usually nd large diculties to test their work. Comparisons among dierent researches in this eld are often a hard task, due to the ambiguity or lack of detail in the presentation of the work and its results. On many occasions, the replication of the work conducted by other researchers is required, which leads to a waste of time and a delay in the research advances. The authors of this study propose a procedure to introduce new techniques and their results in the eld of routing problems. In this paper this procedure is detailed, and a set of good practices to follow are deeply described. It is noteworthy that this procedure can be applied to any combinatorial optimization problem. Anyway, the literature of this study is focused on routing problems. This eld has been chosen because of its importance in real world, and its relevance in the actual literature

Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP)

In the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP), the group of routes to be developed to satisfy the demand of the customer must be determined, considering the minimization of the total costs of the travelled distance. Heuristic algorithms based on local searches use simple movements (neighborhoods) to generate feasible solutions to problems related to route design. In this article, we conduct a comparative analysis of granular neighborhoods in a Tabu Search for the HFVRP, in terms of the quality of the obtained solution. The computational experiments, performed on instances of benchmarking for the HFVRP, showed the efficiency and effectiveness of implementing some neighborhoods in metaheuristic algorithms of path, such as the Tabu Search

An optimized scalable multi-ant colony system for multi-depot vehicle routing problems using a reactive multi-agent system

The multi-depot vehicle routing problem is a variant of the vehicle routing problem that tries to minimize the total cost of providing the service from several depots to satisfy several client demands. This paper presents a multi-ant colony system to solve the multi-depot vehicle routing problem using a reactive agent-based approach. This approach is designed to effectively solve the problem, in which each reactive agent is inspired by modeling the behavior of the ant. We define two types of reactive agents whose behavior differs in the use of two kinds of pheromone trail. In order to refer to the two phases of the execution process, i.e., the assignment phase and the routing phase, every reactive agent cooperates with others to provide a scalable solution for the overall problem. The solution of the multi-depot vehicle routing problem is beneficial and helpful for many real applications. The performance evaluation of the proposed approach is done using instances from the literature, and the results obtained demonstrate good performance when compared with other approaches

Desempeño de las técnicas de agrupamiento para resolver el problema de ruteo con múltiples depósitos

El problema de ruteo de vehículos considerando múltiples depósitos es clasificado como NP duro, cuya solución busca determinar simultáneamente las rutas de un conjunto de vehículos, atendiendo un conjunto de clientes con una demanda determinada. La función objetivo del problema consiste en minimizar el total de la distancia recorrida por las rutas, teniendo en cuenta que todos los clientes deben ser atendidos cumpliendo restricciones de capacidad de depósitos y vehículos. En este artículo se propone una metodología híbrida que combina las técnicas aglomerativas de clusterización para generar soluciones iniciales con un algoritmo de búsqueda local iterada, iterated location search (ILS) para resolver el problema. Aunque en trabajos previos se proponen los métodos de clusterización como estrategias para generar soluciones de inicio, en este trabajo se potencia la búsqueda sobre el sistema de información obtenido después de aplicar el método de clusterización. Además se realiza un extenso análisis sobre el desempeño de las técnicas de clusterización y su impacto en el valor de la función objetivo. El desempeño de la metodología propuesta es factible y efectivo para resolver el problema en cuanto a la calidad de las respuestas y los tiempos computacionales obtenidos, sobre las instancias de la literatura evaluadas.The vehicle routing problem considering multiple depots is classified as NP-hard. MDVRP determines simultaneously the routes of a set of vehicles and aims to meet a set of clients with a known demand. The objective function of the problem is to minimize the total distance traveled by the routes given that all customers must be served considering capacity constraints in depots and vehicles. This paper presents a hybrid methodology that combines agglomerative clustering techniques to generate initial solutions with an iterated local search algorithm (ILS) to solve the problem. Although previous studies clustering methods have been proposed like strategies to generate initial solutions, in this work the search is intensified on the information generated after applying the clustering technique. Besides an extensive analysis on the performance of techniques, and their effect in the final solution is performed. The operation of the proposed methodology is feasible and effective to solve the problem regarding the quality of the answers and computational times obtained on request evaluated literature