Integrated Supply Chain Network Design: Location, Transportation, Routing and Inventory Decisions

abstract: In this dissertation, an innovative framework for designing a multi-product integrated supply chain network is proposed. Multiple products are shipped from production facilities to retailers through a network of Distribution Centers (DCs). Each retailer has an independent, random demand for multiple products. The particular problem considered in this study also involves mixed-product transshipments between DCs with multiple truck size selection and routing delivery to retailers. Optimally solving such an integrated problem is in general not easy due to its combinatorial nature, especially when transshipments and routing are involved. In order to find out a good solution effectively, a two-phase solution methodology is derived: Phase I solves an integer programming model which includes all the constraints in the original model except that the routings are simplified to direct shipments by using estimated routing cost parameters. Then Phase II model solves the lower level inventory routing problem for each opened DC and its assigned retailers. The accuracy of the estimated routing cost and the effectiveness of the two-phase solution methodology are evaluated, the computational performance is found to be promising. The problem is able to be heuristically solved within a reasonable time frame for a broad range of problem sizes (one hour for the instance of 200 retailers). In addition, a model is generated for a similar network design problem considering direct shipment and consolidation within the same product set opportunities. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.Dissertation/ThesisPh.D. Industrial Engineering 201

Comparing fast VRP algorithms for collaborative urban freight transport systems: a solution probleming analysis

International audienceThis paper proposes a comparison between two fast heuristic algorithms to solve a multi-carrier 2E-VRP in city logistics, under realistic conditions. We propose a cluster-first route second algorithm to compare the performance of two route construction and post-optimization algorithms on real-size test cases. The clustering phase is made by a seep algorithm, which defines the number of used vehicles and assigns a set of customers to it. Then, for each cluster, which represents a vehicle, we build a min-cost route by the two following methods. The first is a semi-greedy algorithm. The second is a genetic algorithm that includes post-optimization at the level of each route. In this work we make the route construction and post-optimization without any possible exchange of the routes to guaranty a pertinent comparison between both algorithms. After presenting both approaches, we apply them, first to classical 2E-CVRP instances to state on the algorithm capabilities, then on real-size instances to compare them. Computational results are presented and discussed. Finally, practical implications are addressed

Integrating Dock-Door Assignment and Vehicle Routing in Cross-Docking

Cross-docking is a logistic strategy in which products arrive at terminals, are handled and then shipped to the corresponding destinations. Cross-docking consists of unloading products from inbound trucks and loading these products directly into outbound trucks with little or no storage in-between. Cross-docking aims to reduce or eliminate inventory by achieving an efficient synchronization of unloading trucks, material handling and loading trucks. This thesis introduces an integrated dock-door assignment and vehicle routing problem that consists of assigning a set of origin points to inbound doors at the cross-dock, consolidating commodities in-between inbound and outbound doors, and routing vehicles from outbound doors to destination points. The objective is to minimize the sum of the material handling cost at the cross-dock and the transportation cost for routing the commodities to their destinations. Five mixed integer programming formulations are presented and computationally compared. A column generation algorithm based on a set partitioning formulation is developed to obtain lower bounds on the optimal solution value. In addition, a heuristic algorithm is used to obtain upper bounds. Computational experiments are performed to assess the performance of the proposed MIP formulations and solution algorithms on a set of randomly generated instances

Cost Optimisation in Freight Distribution with Cross-Docking: N-Echelon Location Routing Problem

Freight transportation constitutes one of the main activities that influence the economy and society, as it assures a vital link between suppliers and customers and represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transportation companies in an aim of cost reduction. Although vehicle routing problems are very common in operational research, they are essentially related to single-echelon cases. This paper presents the main concepts of multi-echelon distribution with cross-docks and a unified notation for the N-echelon location routing problem. A literature review is also presented, in order to list the main problems and methods that can be helpful for scientists and transportation practitioners

Cost Optimisation in Freight Distribution with Cross-Docking: N-Echelon Location Routing Problem

Freight transportation constitutes one of the main activities that influence the economy and society, as it assures a vital link between suppliers and customers and represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transportation companies in an aim of cost reduction. Although vehicle routing problems are very common in operational research, they are essentially related to single-echelon cases. This paper presents the main concepts of multi-echelon distribution with cross-docks and a unified notation for the N-echelon location routing problem. A literature review is also presented, in order to list the main problems and methods that can be helpful for scientists and transportation practitioners

Cross-docking with vehicle routing problem. A state of art review 1

Este artículo presenta una revisión al estado del arte durante los últimos diez años, de la literatura relacionada con las plataformas de intercambio logísticas, denominadas Cross-Docking. Este tipo de sistemas surgen como alternativa para reducir el costo logístico y el tiempo de respuesta al cliente. El objetivo consiste en simplificar algunos procesos tales como almacenamiento y manejo de materiales, a partir de la reducción de períodos de bodegaje y realización de surtida de materiales en los muelles de ingreso y salida de mercancía. En la primera parte, se desarrolla el concepto, su funcionamiento operativo y clasificación. En la segunda parte, se realiza un reporte de los trabajos más relevantes acerca de esta técnica. Posteriormente, se profundiza en este tema y el ruteo de vehículos simultáneos, haciendo énfasis en los métodos de solución, puesto que se trata de un problema de optimización combinatoria, clasificado como de alta complejidad computacional. Al final, se presentan conclusiones y la discusión.This article reviews the state of the art for the last ten years about the literature related to Cross-Docking. The Cross-Docking systems emerge as an alternative to reduce logistics costs and customer response time in some processes such as warehousing and material handling, times by reducing storage and picking, on the docks of inbound and outbound of vehicles. In the first part, the concept of Cross-Docking is developed, also its operating performance and classification. In the second part, a report on the most relevant works is done. Subsequently, it delves into the issue of vehicle routing and Cross-Docking with emphasis on methods of solution, since it is a combinatorial optimization problem classified as NP-hard. The document ends with the conclusions and discussion

Cross-Docking: A Proven LTL Technique to Help Suppliers Minimize Products\u27 Unit Costs Delivered to the Final Customers

This study aims at proposing a decision-support tool to reduce the total supply chain costs (TSCC) consisting of two separate and independent objective functions including total transportation costs (TTC) and total cross-docking operating cost (TCDC). The full-truckload (FT) transportation mode is assumed to handle supplier→customer product transportation; otherwise, a cross-docking terminal as an intermediate transshipment node is hired to handle the less-than-truckload (LTL) product transportation between the suppliers and customers. TTC model helps minimize the total transportation costs by maximization of the number of FT transportation and reduction of the total number of LTL. TCDC model tries to minimize total operating costs within a cross-docking terminal. Both sub-objective functions are formulated as binary mathematical programming models. The first objective function is a binary-linear programming model, and the second one is a binary-quadratic assignment problem (QAP) model. QAP is an NP-hard problem, and therefore, besides a complement enumeration method using ILOG CPLEX software, the Tabu search (TS) algorithm with four diversification methods is employed to solve larger size problems. The efficiency of the model is examined from two perspectives by comparing the output of two scenarios including; i.e., 1) when cross-docking is included in the supply chain and 2) when it is excluded. The first perspective is to compare the two scenarios’ outcomes from the total supply chain costs standpoint, and the second perspective is the comparison of the scenarios’ outcomes from the total supply chain costs standpoint. By addressing a numerical example, the results confirm that the present of cross-docking within a supply chain can significantly reduce total supply chain costs and total transportation costs

An Inventory Routing Problem with Cross-Docking

This thesis concerns inventory-transportation tradeoffs in which a number of suppliers serve multiple customers, each ordering several product types. The goal is to design optimal routes to satisfy the customers’ demands. In the proposed approach, the products are shipped to cross-docks from the suppliers, and several customers will be served by each route beginning at a cross-dock. The objective is to minimize the total cost, beginning with summing the transportation costs on those edges through which trips may go, times the shipment frequencies. The holding costs at customers, and the pipeline inventory costs on the routes, take into account that various products may have different carrying-cost parameters. Based on some analytical results, the developed model is reformulated in terms of a single set of decision variables. The holding cost makes the objective function highly nonlinear. In addition, transportation cost and pipeline inventory cost are quadratic. After linearization of the objective function, a column generation algorithm is proposed to solve the nonlinear mixed-integer programming model. The holding cost, which is the sum of a set of fractions, is linearized after objective-function decomposition. Each of the decomposed sub-problems has only one fraction, which can be linearized by replacing that fraction by a new decision variable and adding some constraints to the formulation. To linearize the quadratic parts of the objective function, we substitute a new variable for the multiplication of each pair of decision variables, and add some new constraints. We provide computational results for the model with a single product. All parameters are generated randomly. Our proposed algorithm can optimally solve some problems with up to 626 edges. However, CPU time might be very high. For instances with 500 edges, CPU time can be up to 20 hours depending on the number of iterations the algorithm needs to find the optimal solution. Instances with up to 300 edges are solved to optimality within a CPU time of only one hour on a computer with 16 GB RAM and 3.40 GHz CPU.1 yea

Résolution de problèmes de tournées avec synchronisation : applications au cas multi-échelons et au cross-docking

Transportation systems are more and more interconnected, this has lead to a new kind of constraints, called synchronization constraints, in vehicle routing problems. In this thesis, we study two cases in which this type of constraints arises. First, we propose a heuristic method for a two-echelon problem arising in City Logistics. Second, we study the integration of a cross-dockin pickup and delivery vehicle routing problems. To that end we propose a matheuristic for the vehicule routing problem with cross-docking, and we propose an extension of this problem that integrates specific resource synchonization constraints arising at the cross-dock. A method for a 3D loading problem is also presented.L’interconnexion croissante dans les systèmes de transports a conduit à la modélisation de nouvelles contraintes, dites contraintes de synchronisation, dans les problèmes de tournées de véhicules. Dans cette thèse, nous nous intéressons à deux cas dans lesquels ce type de problématiques apparaît. Dans un premier temps, nous proposons une méthode heuristique pour un problème à deux échelons rencontré pour la distribution de marchandises en ville. Dans un second temps, nous étudions l’intégration d’un cross-dock dans des tournées de collectes et livraisons. Une première contribution à ce sujet concerne le problème de tournées de véhicules avec cross-docking, et une seconde contribution intègre, en plus, des contraintes de ressources au cross-dock dans le problème de routage. Une méthode pour un problème de chargement 3D, étudié lors d’un stage doctoral en entreprise, est également présentée