A state of the art and a general formulation model of Hub Location-Routing Problems for LTL shipments

National audienceIn many logistic systems for less than truckload (LTL) shipments, transportation of goods from one origin to its destination is made through collection tours to a hub and delivery tours from the same or another hub, while the goods are shipped between two hubs using Full Truckload (FTL) shipments. Therefore, managers need to determine the location of the hubs, the allocation of non-hub nodes, and the optimal collection and delivery routes within the network. This problem, known as the hub location-routing problem (HLRP), is related to both the hub location problem (HLP) and the location-routing problem (LRP). The HLP involves the location of hub facilities concentrating flows in order to take advantage of economies of scale and through which flows are to be routed from origins to destinations. The objective of the HLRP is to minimize the total costs including hub costs, inter-hub transportation costs, and collection/distribution routing costs. Based on the literatures review, the aims of this paper are to analyze the state of the art, propose some generic mathematical models for the HLRP and implement some tests using a MIP solver

Network hub locations problems: the state of the art

Cataloged from PDF version of article.Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature. (C) 2007 Elsevier B.V. All rights reserved

Applying VNPSO Algorithm to Solve the Many-to-Many Hub Location-Routing Problem in a Large scale

One way to increase the companies’ performance and reducing their costs is to concern the transportation industry. Many-to-many hub location-routing problem (MMHLRP) is one of the problems that can affect the process of transportation costs. The problem of MMHLRP is one of the NP-HARD problems. Hence, solving it by exact methods is not affordable; however it was first solved by Benders decomposition algorithm. Modeling and the solving algorithm is able to solve the problem with 100 nodes. In this study, using VNPSO (a combination of the two methods VNS and PSO) was suggested to solve MMHLRP in large-scale. Given high similarity of the results obtained in small scale, using a random sample confirmed that the proposed method was able to solve problem MMHLRP with 300 nodes and acceptable accuracy and speed

A hub covering model for cargo delivery systems

The hub location problem appears in a variety of applications including airline systems, cargo delivery systems, and telecommunication network design. When we analyze the application areas separately, we observe that each area has its own characteristics. In this research we focus on cargo delivery systems. Our interviews with various cargo delivery firms operating in Turkey enabled us to determine the constraints, requirements, and criteria of the hub location problem specific to the cargo delivery sector. We present integer programming formulations and large-scale implementations of the models within Turkey. The results are compared with the current structure of a cargo delivery firm operating in Turkey. © 2006 Wiley Periodicals, Inc

Modular Hub Location Problems

Hub location problems deal with the location of a set of hub facilities and the design of the network so as to provide the most cost-effective way to route a set of commodities through the network. In this thesis we present the Modular Hub Location Problem (MHLP). The MHLP differs from classical hub location problems in the way the economies of scale are modeled. The MHLP considers a step-wise cost function to model the flow dependency of transportation costs at the links of the network. We propose four variants of the MHLP: single allocation and multiple allocation versions with the assumption of having direct connections or not for each case. Computational experiments are performed on benchmark instances in order to evaluate the efficiency and limitations of the considered models

INTEGRATED HUB LOCATION AND CAPACITATED VEHICLE ROUTING PROBLEM OVER INCOMPLETE HUB NETWORKS

Hub location problem is one of the most important topics encountered in transportation and logistics management. Along with the question of where to position hub facilities, how routes are determined is a further challenging problem. Although these two problems are often considered separately in the literature, here, in this study, the two are analyzed together. Firstly, we relax the restriction that a vehicle serves between each demand center and hub pair and propose a mixed-integer mathematical model for the single allocation p-hub median and capacitated vehicle routing problem with simultaneous pick-up and delivery. Moreover, while many studies in hub location problem literature assume that there is a complete hub network structure, we also relax this assumption and present the aforementioned model over incomplete hub networks. Computational analyses of the proposed models were conducted on various instances on the Turkish network. Results indicate that the different capacity levels of vehicles have an important impact on optimal hub locations, hub arc networks, and routing design

A New Model for The Multi-Objective Multiple Allocation Hub Network Design and Routing Problem

In this paper, we propose a new model for the multi-objective multiple allocation hub network design and routing problem which contains determining the location of hubs, the design of hub network, and the routing of commodities between source-destination pairs in the given network. The selected hubs are not assumed to be fully connected, and each node and arc in the network has capacity constraints. The multiple objectives of the problem are the minimization of total xed and transportation costs and the minimization of the maximum travel time required for routing. We propose a mathematical formulation for the multiobjective problem and present a meta-heuristic solution based on a well-known multi-objective evolutionary algorithm. Using the proposed formulation, we are able to nd the optimal solution for small networks of ve nodes and seven nodes. To evaluate the performance of our heuristic approach on real data, the computational experiments are conducted on Turkish postal system data set. The results demonstrate that our heuristic approach can nd feasible solutions to the problem in reasonable execution time, which is less than 10 min

Applying VNPSO Algorithm to Solve the Many-to-Many Hub Location-Routing Problem in a Large scale

One way to increase the companies’ performance and reducing their costs is to concern the transportation industry. Many-to-many hub location-routing problem (MMHLRP) is one of the problems that can affect the process of transportation costs. The problem of MMHLRP is one of the NP-HARD problems. Hence, solving it by exact methods is not affordable; however it was first solved by Benders decomposition algorithm. Modeling and the solving algorithm is able to solve the problem with 100 nodes. In this study, using VNPSO (a combination of the two methods VNS and PSO) was suggested to solve MMHLRP in large-scale. Given high similarity of the results obtained in small scale, using a random sample confirmed that the proposed method was able to solve problem MMHLRP with 300 nodes and acceptable accuracy and speed