Distribution planning in a weather-dependent scenario with stochastic travel times: a simheuristics approach

In real-life logistics, distribution plans might be affected by weather conditions (rain, snow, and fog), since they might have a significant effect on traveling times and, therefore, on total distribution costs. In this paper, the distribution problem is modeled as a multi-depot vehicle routing problem with stochastic traveling times. These traveling times are not only stochastic in nature but the specific probability distribution used to model them depends on the particular weather conditions on the delivery day. In order to solve the aforementioned problem, a simheuristic approach combining simulation within a biased-randomized heuristic framework is proposed. As the computational experiments will show, our simulation-optimization algorithm is able to provide high-quality solutions to this NP-hard problem in short computing times even for large-scale instances. From a managerial perspective, such a tool can be very useful in practical applications since it helps to increase the efficiency of the logistics and transportation operations.Peer ReviewedPostprint (published version

Distribution planning in a weather-dependent scenario with stochastic travel times: a simheuristics approach

In real-life logistics, distribution plans might be affected by weather conditions (rain, snow, and fog), since they might have a significant effect on traveling times and, therefore, on total distribution costs. In this paper, the distribution problem is modeled as a multi-depot vehicle routing problem with stochastic traveling times. These traveling times are not only stochastic in nature but the specific probability distribution used to model them depends on the particular weather conditions on the delivery day. In order to solve the aforementioned problem, a simheuristic approach combining simulation within a biased-randomized heuristic framework is proposed. As the computational experiments will show, our simulation-optimization algorithm is able to provide high-quality solutions to this NP-hard problem in short computing times even for large-scale instances. From a managerial perspective, such a tool can be very useful in practical applications since it helps to increase the efficiency of the logistics and transportation operations.Peer ReviewedPostprint (published version

A Modelling of Genetic Algorithm for Inventory Routing Problem Simulation Optimisation

This paper presents the simulation optimization modelling for Inventory Routing Problem (IRP) using Genetic Algorithm method. The IRP simulation model is based on the stochastic periodic Can-Deliver policy that allows early replenishment for the retailers who have reached the can-deliver level and consolidates the delivery with other retailers that have reached or fallen below the must-deliver level. The Genetic Algorithm is integrated into the IRP simulation model as optimizer in effort to determine the optimal inventory control parameters that minimized the total cost. This study implemented a Taguchi Method for the experimental design to evaluate the GA performance for different combination of population and mutation rate and to determine the best parameters setting for GA with respect to the computational time and best generation number on determining the optimal inventory control. The result shows that the variations of the mutation rate parameter significantly affect the performance of IRP model compared to population size at 95% confidence level. The implementation of elite preservation during the mutation stage is able to improve the performance of GA by keeping the best solution and used for generating the next population. The results indicated that the best generation number is obtained at GA configuration settings on large population sizes (100) with low mutation rates(0.08). The study also affirms the premature convergence problem faced in GA that required improvement by integrating with the neighbourhood search approach

Collector Managed Inventory, A Proactive Planning Approach to the Collection of Liquids coming from End-of-life Vehicles

In this article we introduce Collector Managed Inventory (CMI) as the reverse logistics counter part of Vendor Managed Inventory (VMI).The collection company takes responsibility for the inventories of cores or materials to be recycled.Experience in forward supply chain management has shown the potential of VMI by bringing the coordination of transportation and inventory decisions to the same supply chain entity.Using information technology called telemetry, we are able to monitor inventory levels at distance.We introduce a proactive planning methodology based on two types of collection orders: must- and can-orders.Every collection period all must-orders have to be collected, while canorders are only collected if they can be combined beneficially with the must-orders.The routing problem is solved by a combination of route generation and set partitioning.The system is illustrated in a real-life case study for Auto Recycling Nederland on the collection of liquids coming from end-oflife vehicles, such as coolant and oil.In several scenarios the old reactive approach is compared to the proactive approach resulting in cost savings up to about 19%.supply;logistics;vehicle routine;distribution;information technology;inventory

Genetic algorithm for the continuous location-routing problem

This paper focuses on the continuous location-routing problem that comprises of the location of multiple depots from a given region and determining the routes of vehicles assigned to these depots. The objective of the problem is to design the delivery system of depots and routes so that the total cost is minimal. The standard location-routing problem considers a finite number of possible locations. The continuous location-routing problem allows location to infinite number of locations in a given region and makes the problem much more complex. We present a genetic algorithm that tackles both location and routing subproblems simultaneously.Web of Science29318717

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

Gestión logística de sistemas de hospitalización domiciliaria: una revisión crítica de modelos y métodos

RESUMEN: Los servicios de Hospitalización Domiciliaria (HD) se basan en una red de distribución, en la cual los pacientes son hospitalizados en sus casas y los prestadores de servicios de salud deben entregar cuidados médicos coordinados a los pacientes. La demanda de estos servicios está creciendo rápidamente y los gobiernos y proveedores de servicios de salud enfrentan el reto de tomar un conjunto de decisiones complejas en un sector con un componente logístico importante. En este artículo se presenta una revisión crítica de los modelos y métodos utilizados para darle soporte a las decisiones logísticas en HD. Para esto se presenta primero un marco de referencia, con el objetivo de identificar las oportunidades de investigación en el campo. Con base en dicho marco, se presenta la revisión de la literatura y la identificación de brechas en la investigación. En particular, se hace énfasis en la necesidad de desarrollar e implementar metodologías más integradas para dar soporte a las decisiones estratégicas y tácticas y de considerar puntos clave de los sistemas reales.ABSTRACT: Home Health Care (HHC) services are based on a delivery network in which patients are hospitalized at their homes and health care providers must deliver coordinated medical care to patients. Demand for HHC services is rapidly growing and governments and health care providers face the challenge to make a set of complex decisions in a medical service business that has an important component of logistics problems. The objective of this paper is to provide a critical review of models and methods used to support logistics decisions in HHC. For this purpose, a reference framework is proposed first in order to identify research perspectives in the field. Based on this framework, a literature review is presented and research gaps are identified. In particular, the literature review reveals that more emphasizes is needed to develop and implement more integrated methodologies to support decisions at tactical and strategic planning levels and to consider key features from real systems

Inventory routing problem with stochastic demand and lead time

In the supply chain, the integration of the different processes is critical to obtain high levels of coordination. Inventory control and its distribution are two of these processes whose coordination have been demonstrated by researchers as key in order to gain efficiency and effectiveness. They affect the synchronization of the supply chain management. With the intention to contribute to the integration of these processes and improve the problems of demand variability, we propose an integration of operations research area and the help of metaheuristics in a multi-objective approach. The expected results are to reduce the costs associated with inventory and its distribution, as well as to reduce the uncertainty in making decisions based on demand. This thesis presents methods for obtaining and analyzing near optimally solutions for dynamic and stochastic inventory-routing problems. The methods include retailers selection and clustering methods, algorithms and experiments on benchmark instances. We focus on problems with one and several suppliers that serve several dispersal geographically retailers. The thesis contains four parts. In Part I, we focus on the literature review. We first provide an overview of the literature on problems related to the coordination of the inventory and its distribution. Then we make a point in four elements: information management, inventory policies, stochastic demand and optimization methods. Also, we provide a scientometric analysis of the documentation collected in the last ten years. We provide a thorough review of papers working with dynamic and stochastic demand. The contributions of this part are i) the review of papers working with stochastic demand and stochastic lead times focusing on its stochastic and multi-depot aspects, ii) identify critical factors for the performance of many logistics activities and industries, iii) have shown that studying the behavior of the demand and the lead time are essential in order to achieve a useful representation of the system to take proper decisions and iv) provide the trends and patterns in the research in IRP problems. In Part II, we focus on the methodology of the research and of development. We first introduce the problem, state of the science, the gaps in the literature, variables under study, the instruments applied and assumptions. The development methodology is presented by a general model to address this type of research proposed in this thesis. Here, the general development process, decomposition of the problem and how the possible solutions are explained.. The importance of the this chapter is provided an effective way to face IRP problems. In Part III, the foundations in formulations for IRP problems are proposed. We begin with the formulation of the TSP problems with variants for one and many suppliers, likewise for VRP and IRP problems. The contributions of the model presented here aim identifying the variables and mathematical models frequently used to deal with these problems. In Part IV, we perform a single criteria objective and multi-criteria analysis of the solutions for one and many suppliers instances. Our methods yield significant improvements over a competing algorithm. Our contributions are i) propose three new customer selection methods for a dynamic and stochastic inventory-routing vii problem, ii) perform a multi-criteria analysis of the solutions, comparing distribution versus inventory management, iii) perform a single criteria objective experiment on benchmark instances from the literature.En la cadena de suministro, la integración de los diferentes procesos que la conforman, es fundamental para obtener altos niveles de coordinación. El control del inventario y su distribución son dos de estos procesos, cuya coordinación ha sido demostrada por los investigadores como clave para lograr mejoras en eficiencia y efectividad. Estos a su vez, afectan la sincronización y la administración de la cadena de suministro. Con el propósito de contribuir en la integración de éstos procesos y mejorar los problemas derivados de la variabilidad de la demanda, se propone usar los fundamentos del área de investigación de operaciones y la ayuda de metaheurísticas en un enfoque multi-obejtivo. Los resultados esperados son reducir los costos asociados a los procesos de inventario y distribución, así como también reducir la incertidumbre en la toma de decisiones a partir de la demanda. Ésta tesis presenta métodos para el análisis y obtención de soluciones cercanas a las óptimas para problemas de inventario y routeo, dinámico y estocástico. Los métodos incluyen selección de retailers y métodos de clustering, algoritmos y experimentos en instancias de prueba disponibles en la literatura. Se hace énfasis en instancias de un solo proveedor y varios proveedores que sirven varios retailers distribuidos geográficamente. La tesis está organizada en cuatro partes. En la Parte I, se revisa la literatura, para ello, primero se presentan los problemas relacionados con la coordinación del inventario y su distribución. Ésta revisión resalta cuatro elementos que han sido identificados como claves en la literatura como son: la administración de la información, políticas de inventario, demanda estocástica y métodos de optimización. Luego, se presenta un análisis cienciometrico de la literatura encontrada en los últimos 10 años. La revisión de la documentación se realiza de manera exhaustiva trabajando con demanda dinámica y estocástica. Las contribuciones de esta parte son: i) proporcionar una revisión pertinente y actualizada de artículos que emplean demanda estocástica, enfatizando en sus elementos dinámicos y estocásticos, así como también en aspectos que permitan abordar problemas con múltiples depósitos, ii) identificar factores críticos para el desempeño de actividades logísticas, iii) Demostrar que el estudio de la demanda es esencial para lograr una representación útil del sistema, la cual influye en la toma de decisiones y iv) proporcionar tendencias y patrones en la investigación de problemas de IRP. En la Parte II se aborda la metodología de la investigación y de desarrollo. Primero, se presenta el problema, el estado de la ciencia y los gaps encontrados en la literatura. Luego se identifican las variables de estudio, los instrumentos aplicados y los supuestos utilizados. La metodología de desarrollo es presentada por medio de un modelo general para abordar éste tipo de investigaciones que nosotros proponemos en ésta tesis. Esta metodología aborda aspectos como: el procedimiento general de desarrollo, la descomposición del problema y la forma en que se prueban las posibles soluciones. En la Parte III, se presentan los fundamentos en la formulación de IRP. Primero se formulan los problemas TSP con variantes para un solo depósito y también paramúltiples depósitos, igualmente se hace para VRP e IRP. La contribución de los modelos presentados son la identificación de las variables y los modelos matemáticos que frecuentemente son usados para tratar con éste tipo de problemas. En la Parte IV se presentan dos experimentos. El primero para el análisis de instancias con uno sólo depósito y en el segundo para analizar instancias con múltiples depósitos. Los métodos usados producen mejoras sobre resultados obtanidos con algoritmos similares. Las contribuciones de ésta parte son: i) proponer tres nuevos métodos para la selección de retailers para IRP dinámicos y estocásticos, ii) realizar análisis multi-criterio de las soluciones, comparando la distribución con la administración del inventario y iii) realizar análisis de un solo objetivo sobre instancias de pruebas proporcionada por la literatura existente