Simulation and optimization methods for logistics pooling in the outbound supply chain

Logistics pooling and collaborative transportation systems are relatively new concepts in logistics research, but are very popular in practice. This communication proposes a conceptual framework for logistics and transportation pooling systems, as well as a simulation method for strategic planning optimization. This method is based on a twostep constructive heuristic in order to estimate for big instances the transportation and storage costs at a macroscopic level. Four possible scenarios are explored and commented. Finally, a socio-economic analysis based on 20 semi-directive interviews is presented to propose the limitations and obstacles of logistics poolingLogistics pooling, supply chain management, optimization, group reasoning, simulation

Cross-docking: A systematic literature review

This paper identifies the major research concepts, techniques, and models covered in the cross-docking literature. A systematic literature review is conducted using the BibExcel bibliometric analysis and Gephi network analysis tools. A research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis are used to identify the primary research themes. The RFPN results suggest that vehicle routing, inventory control, scheduling, warehousing, and distribution are most studied. Of the optimization and simulation techniques applied in cross-docking, linear and integer programming has received much attention. The paper informs researchers interested in investigating cross-docking through an integrated perspective of the research gaps in this domain. This paper systematically reviews the literature on cross-docking, identifies the major research areas, and provides a survey of the techniques and models adopted by researchers in the areas related to cross-docking

Scheduling cross-docking operations under uncertainty: A stochastic genetic algorithm based on scenarios tree

A cross-docking terminal enables consolidating and sorting fast-moving products along supply chain networks and reduces warehousing costs and transportation efforts. The target efficiency of such logistic systems results from synchronizing the physical and information flows while scheduling receiving, shipping and handling operations. Within the tight time-windows imposed by fast-moving products (e.g., perishables), a deterministic schedule hardly adheres to real-world environments because of the uncertainty in trucks arrivals. In this paper, a stochastic MILP model formulates the minimization of penalty costs from exceeding the time-windows under uncertain truck arrivals. Penalty costs are affected by products' perishability or the expected customer’ service level. A validating numerical example shows how to solve (1) dock-assignment, (2) while prioritizing the unloading tasks, and (3) loaded trucks departures with a small instance. A tailored stochastic genetic algorithm able to explore the uncertain scenarios tree and optimize cross-docking operations is then introduced to solve scaled up instaces. The proposed genetic algorithm is tested on a real-world problem provided by a national delivery service network managing the truck-to-door assignment, the loading, unloading, and door-to-door handling operations of a fleet of 271 trucks within two working shifts. The obtained solution improves the deterministic schedule reducing the penalty costs of 60%. Such results underline the impact of unpredicted trucks’ delay and enable assessing the savings from increasing the number of doors at the cross-dock

Enrutamiento de almacenes cruzados considerando ventanas de tiempo y precios de ruta (estudio de caso: transporte de contenedores del puerto de Chabahar)

In this study, we develop a model for routing cross-docking centers considering time windows and pricing routs. In this model picking and delivery in several times is permitted and each knot can be serviced by more than one vehicle. Every truck can transport one or more product, in other words, we consider compatibility between product and vehicle. This model includes two goals: reducing the total cost and reducing the cost of carrying goods (freight fare). The total cost includes the cost required to traverse between the points, the cost of traversing the routes between the central cross-docking center and the first points after moving, and the cost to traverse the routes between the last points in each route and the depots that must be minimized. In general, the purpose of the model is to obtain the number of cross-docking center, the number of vehicles and the best route in the distribution network. We present a nonlinear programming model for this problem. We have solved the proposed model by GAMS. As the dimensions of the problem increase, the implementation time of the program increases progressively. So, in order to solve the model in medium and large scales, we proposed a genetic meta-heuristic algorithm. The results of examining different issues by the meta-heuristic approach show the very high efficiency of the developed algorithms in terms of the solution time and the answer of the problem.En esta investigación, se presenta un modelo para el enrutamiento entre almacenes con ventanas de tiempo y precios de ruta. En este modelo, se permite la recogida y entrega en varias ocasiones y cada nodo puede recibir servicio con más de un vehículo. Cada camión puede transportar uno o más tipos de mercancías, es decir, se considera la compatibilidad entre la mercancía y el vehículo. En este modelo, hay dos objetivos, que incluyen reducir el costo total y reducir el precio de envío de mercancías (flete). El costo total incluye el costo de recorrer los senderos entre los puntos, el costo de recorrer los senderos entre el almacén de la intersección central y los primeros puntos después de la salida, y el costo de recorrer los senderos entre los últimos puntos de cada sendero y los almacenes que deben minimizarse. En general, el propósito del modelo es obtener el número de almacenes, el número de vehículos y la mejor ruta en la red de distribución. Y presentamos un modelo de programación no lineal para este problema. Hemos resuelto el modelo propuesto con GAMS. A medida que aumenta el tamaño del problema, el tiempo de ejecución del programa aumenta considerablemente. Por tanto, para resolver el modelo en medianas y grandes dimensiones, presentamos el algoritmo genético metaheurístico. Los resultados de examinar varios problemas con metaheurísticas muestran la altísima eficiencia de los algoritmos propuestos en términos de tiempo de resolución de problemas

Enrutamiento de almacenes cruzados considerando ventanas de tiempo y precios de ruta (estudio de caso: transporte de contenedores del puerto de Chabahar)

In this study, we develop a model for routing cross-docking centers considering time windows and pricing routs. In this model picking and delivery in several times is permitted and each knot can be serviced by more than one vehicle. Every truck can transport one or more product, in other words, we consider compatibility between product and vehicle. This model includes two goals: reducing the total cost and reducing the cost of carrying goods (freight fare). The total cost includes the cost required to traverse between the points, the cost of traversing the routes between the central cross-docking center and the first points after moving, and the cost to traverse the routes between the last points in each route and the depots that must be minimized. In general, the purpose of the model is to obtain the number of cross-docking center, the number of vehicles and the best route in the distribution network. We present a nonlinear programming model for this problem. We have solved the proposed model by GAMS. As the dimensions of the problem increase, the implementation time of the program increases progressively. So, in order to solve the model in medium and large scales, we proposed a genetic meta-heuristic algorithm. The results of examining different issues by the meta-heuristic approach show the very high efficiency of the developed algorithms in terms of the solution time and the answer of the problem.En esta investigación, se presenta un modelo para el enrutamiento entre almacenes con ventanas de tiempo y precios de ruta. En este modelo, se permite la recogida y entrega en varias ocasiones y cada nodo puede recibir servicio con más de un vehículo. Cada camión puede transportar uno o más tipos de mercancías, es decir, se considera la compatibilidad entre la mercancía y el vehículo. En este modelo, hay dos objetivos, que incluyen reducir el costo total y reducir el precio de envío de mercancías (flete). El costo total incluye el costo de recorrer los senderos entre los puntos, el costo de recorrer los senderos entre el almacén de la intersección central y los primeros puntos después de la salida, y el costo de recorrer los senderos entre los últimos puntos de cada sendero y los almacenes que deben minimizarse. En general, el propósito del modelo es obtener el número de almacenes, el número de vehículos y la mejor ruta en la red de distribución. Y presentamos un modelo de programación no lineal para este problema. Hemos resuelto el modelo propuesto con GAMS. A medida que aumenta el tamaño del problema, el tiempo de ejecución del programa aumenta considerablemente. Por tanto, para resolver el modelo en medianas y grandes dimensiones, presentamos el algoritmo genético metaheurístico. Los resultados de examinar varios problemas con metaheurísticas muestran la altísima eficiencia de los algoritmos propuestos en términos de tiempo de resolución de problemas

A branch-and-price method for the Vehicle Routing Problem with Cross-Docking and Time Windows

One important factor in supply chain management is to efficiently control the supply chain flows. Due to its importance, many companies are trying to develop efficient methods to increase customer satisfaction and reduce costs. Cross-docking is considered a good method to reduce inventory and improve responsiveness. The Vehicle Routing Problem with Cross-Docking and Time Windows (VRP-CD-TW) consists on designing the minimum-cost set of routes to serve a given set of transportation requests while respecting constraints on vehicles capacity, customer time windows and using transfers on a cross-docking base. Each customer must be visited just once and mixed tours comprising pick-up and delivery stops are not allowed. For a given vehicle, the designed pick-up tour must precede its delivery tour. In this work, we model the VRP-CD-TW assuming that all feasible orders are known in advance. We present a new mixed integer program to model the VRP-CD-TW and reformulate it via Dantzig–Wolfe decomposition to later develop a column generation procedure. The proposed branch-and-price algorithm shows encouraging results on solving some Solomon-based instances.Sociedad Argentina de Informática e Investigación Operativ

A Branch-and-price Method for the Vehicle Routing problem with Cross-docking and Time Windows

One important factor in supply chain management is to efficiently control the supply chain flows. Due to its importance, many companies are trying to develop efficient methods to increase customer satisfaction and reduce costs. Cross-docking is considered a good method to reduce inventory and improve responsiveness. The Vehicle Routing Problem with Cross-Docking and Time Windows (VRP-CD-TW) consists on designing the minimum-cost set of routes to serve a given set of transportation requests while respecting constraints on vehicles capacity, customer time windows and using transfers on a cross-docking base. Each customer must be visited just once and mixed tours comprising pick-up and delivery stops are not allowed. For a given vehicle, the designed pick-up tour must precede its delivery tour. In this work, we model the VRP-CD-TW assuming that all feasible orders are known in advance. We present a new mixed integer program to model the VRP-CD-TW and reformulate it via Dantzig-Wolfe decomposition to later develop a column generation procedure. The proposed branch-and-price algorithm shows encouraging results on solving some Solomon-based instances.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentin