Browsing by Subject "P-Hub median"

Now showing 1 - 4 of 4

Open Access
Allocation Strategies in Hub Networks
(Elsevier, 2011-06-11) Yaman, H.
In this paper, we study allocation strategies and their effects on total routing costs in hub networks. Given a set of nodes with pairwise traffic demands, the p-hub median problem is the problem of choosing p nodes as hub locations and routing traffic through these hubs at minimum cost. This problem has two versions; in single allocation problems, each node can send and receive traffic through a single hub, whereas in multiple allocation problems, there is no such restriction and a node may send and receive its traffic through all p hubs. This results in high fixed costs and complicated networks. In this study, we introduce the r-allocation p-hub median problem, where each node can be connected to at most r hubs. This new problem generalizes the two versions of the p-hub median problem. We derive mixed-integer programming formulations for this problem and perform a computational study using well-known datasets. For these datasets, we conclude that single allocation solutions are considerably more expensive than multiple allocation solutions, but significant savings can be achieved by allowing nodes to be allocated to two or three hubs rather than one. We also present models for variations of this problem with service quality considerations, flow thresholds, and non-stop service.
Open Access
The hierarchical hub median problem with single assignment
(Elsevier, 2009) Yaman, H.
We study the problem of designing a three level hub network where the top level consists of a complete network connecting the so-called central hubs and the second and third levels are unions of star networks connecting the remaining hubs to central hubs and the demand centers to hubs and central hubs, respectively. The problem is to decide on the locations of a predetermined number of hubs and central hubs and the connections in order to minimize the total routing cost in the resulting network. This problem includes the classical p-hub median problem as a special case. We also consider a version of this problem where service quality considerations are incorporated through delivery time restrictions. We propose mixed integer programming models for these two problems and report the outcomes of a computational study using the CAB data and the Turkey data.
Open Access
Multimodal hub location and hub network design
(2012) Alumur, S. A.; Kara, B. Y.; Karasan O. E.
Through observations from real life hub networks, we introduce the multimodal hub location and hub network design problem. We approach the hub location problem from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub networks with different possible transportation modes must be designed. In this multimodal hub location and hub network design problem, we jointly consider transportation costs and travel times, which are studied separately in most hub location problems presented in the literature. We allow different transportation modes between hubs and different types of service time promises between origin– destination pairs while designing the hub network in the multimodal problem. We first propose a linear mixed integer programming model for this problem and then derive variants of the problem that might arise in certain applications. The models are enhanced via a set of effective valid inequalities and an efficient heuristic is developed. Computational analyses are presented on the various instances from the Turkish network and CAB data set.
Open Access
Star p-hub median problem with modular arc capacities
(Elsevier, 2008) Yaman, H.
We consider the hub location problem, where p hubs are chosen from a given set of nodes, each nonhub node is connected to exactly one hub and each hub is connected to a central hub. Links are installed on the arcs of the resulting network to route the traffic. The aim is to find the hub locations and the connections to minimize the link installation cost. We propose two formulations and a heuristic algorithm to solve this problem. The heuristic is based on Lagrangian relaxation and local search. We present computational results where formulations are compared and the quality of the heuristic solutions are tested.