Browsing by Subject "Hub location"

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A mean-CVaR approach to the risk-averse single allocation hub location problem with flow-dependent economies of scale
(Elsevier Ltd, 2022-11-29) Ghaffarinasab, Nader; Çavuş, Ö.; Kara, B. Y.
The hub location problem (HLP) is a fundamental facility planning problem with various applications in transportation, logistics, and telecommunication systems. Due to strategic nature of the HLP, considering uncertainty and the associated risks is of high practical importance in designing hub networks. This paper addresses a risk-averse single allocation HLP, where the traffic volume between the origin–destination (OD) pairs is considered to be uncertain. The uncertainty in demands is captured by a finite set of scenarios, and a flow-dependent economies of scale scheme is used for transportation costs, modeled as a piece-wise concave function of flow on all network arcs. The problem is cast as a risk-averse two-stage stochastic problem using mean-CVaR as the risk measure, and a novel solution approach combining Benders decomposition and scenario grouping is proposed. An extensive set of computational experiments is conducted to study the effect of different input parameters on the optimal solution, and to evaluate the performance of the proposed solution algorithm. Managerial insights are derived and presented based on the obtained results.
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
A branch and cut algorithm for hub location problems with single assignment
(Springer, 2005) Labbé, M.; Yaman, H.; Gourdin, E.
The hub location problem with single assignment is the problem of locating hubs and assigning the terminal nodes to hubs in order to minimize the cost of hub installation and the cost of routing the traffic in the network. There may also be capacity restrictions on the amount of traffic that can transit by hubs. The aim of this paper is to investigate polyhedral properties of these problems and to develop a branch and cut algorithm based on these results.
Open Access
A branch-and-cut algorithm for the hub location and routing problem
(Elsevier, 2014) Rodríguez-Martín, I.; Salazar-González, J-J.; Yaman, H.
We study the hub location and routing problem where we decide on the location of hubs, the allocation of nodes to hubs, and the routing among the nodes allocated to the same hubs, with the aim of minimizing the total transportation cost. Each hub has one vehicle that visits all the nodes assigned to it on a cycle. We propose a mixed integer programming formulation for this problem and strengthen it with valid inequalities. We devise separation routines for these inequalities and develop a branch-and-cut algorithm which is tested on CAB and AP instances from the literature. The results show that the formulation is strong and the branch-and-cut algorithm is able to solve instances with up to 50 nodes.
Open Access
A capacitated hub location problem under hose demand uncertainty
(Elsevier, 2017) Meraklı, M.; Yaman, H.
In this study, we consider a capacitated multiple allocation hub location problem with hose demand uncertainty. Since the routing cost is a function of demand and capacity constraints are imposed on hubs, demand uncertainty has an impact on both the total cost and the feasibility of the solutions. We present a mathematical formulation of the problem and devise two different Benders decomposition algorithms. We develop an algorithm to solve the dual subproblem using complementary slackness. In our computational experiments, we test the efficiency of our approaches and we analyze the effects of uncertainty. The results show that we obtain robust solutions with significant cost savings by incorporating uncertainty into our problem.
Open Access
A conditional β -mean approach to risk-averse stochastic multiple allocation hub location problems
(Elsevier Ltd, 2022-01-29) Ghaffarinasab, N.; Yetiş Kara, Bahar
This paper addresses risk-averse stochastic hub location problems where the risk is measured using the conditional β -mean criterion. Three variants of the classical multiple allocation hub location problem, namely the p-hub median, the p-hub maximal covering, and the weighted p-hub center problems are studied under demand data uncertainty represented by a finite set of scenarios. Novel mixed-integer linear programming formulations are proposed for the problems and exact algorithms based on Benders decomposition are developed for solving large instances of the problems. A large set of computational tests are conducted so that the efficiency of the proposed algorithms is proved and the effect of various input parameters on the optimal solutions is analyzed.
Open Access
The design of single allocation incomplete hub networks
(Elsevier, 2009) Alumur, S. A.; Kara, B. Y.; Karasan, O. E.
The hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between any origin-destination pair. In the extensive literature on this challenging network design problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Relaxation of this basic assumption constitutes the starting point of the present work. In this study, we provide a uniform modeling treatment to all the single allocation variants of the existing hub location problems, under the incomplete hub network design. No network structure other than connectivity is imposed on the induced hub network. Within this context, the single allocation incomplete p-hub median, the incomplete hub location with fixed costs, the incomplete hub covering, and the incomplete p-hub center network design problems are defined, and efficient mathematical formulations for these problems with O (n3) variables are introduced. Computational analyses with these formulations are presented on the various instances of the CAB data set and on the Turkish network.
Open Access
Efficient simulated annealing based solution approaches to the competitive single and multiple allocation hub location problems
(Elsevier, 2018) Ghaffarinasab, N.; Motallebzadeh, A.; Jabarzadeh, Y.; Kara, Bahar Y.
Hub location problems (HLPs) constitute an important class of problems in logistics with numerous applications in passenger/cargo transportation, postal services, telecommunications, etc. This paper addresses the competitive single and multiple allocation HLPs where the market is assumed to be a duopoly. Two firms (decision makers) sequentially decide on the configuration of their hub networks trying to maximize their own market shares. The customers choose one firm based on the cost of service provided by these firms. Mathematical formulations are presented for the problems of the first and second firms (the leader and the follower, respectively) and Simulated Annealing (SA) based solution algorithms are proposed for solving these problems both in single and multiple allocation settings. Extensive computational experiments show the capability of the proposed solution algorithms to obtain the optimal solutions in short computational times. Some managerial insights are also derived based on the obtained results.
Open Access
Endogenous effects of hubbing on flow intensities
(Springer, 2016) Taner, M. R.; Kara, B. Y.
Location of hub facilities and the allocation decisions in transport networks endogenously affect both the flow intensities and the transportation costs. Since the introduction of the hub location problem to the operations research literature in mid-1980s, many researchers investigated different ways of modelling the effects of hub facilities on the transportation costs. On the other hand, there has been very limited research on their effect on the flow intensities. This study proposes a new approach, inspired by the Bass diffusion model, to forecast the change in the demand patterns generated at different locations as a result of the placement of new hubs. This new model is used in the context of the uncapacitated single allocation p-hub median problem to investigate the effects of endogenous attraction, caused by the spatial interaction of present hubs, on future hub location decisions. Computational results indicate that the location and allocation decisions may be greatly affected when these forecasts are taken into account in the selection of future hub locations.
Open Access
Green hub location problem
(Elsevier, 2019) Dükkancı, Okan; Peker, Meltem; Kara, Bahar Y.
This paper introduces the green hub location problem that finds the best locations for hubs, assignments of demand nodes to these hubs and speed of trucks/flights so as to route the demand between any origin-destination pairs. The aim of the service provider is to minimize the total amount of emissions that depends on vehicle speed and payload while routing the deliveries within a predetermined service time limit. In this study, we first propose a nonlinear model for this problem, which is then reformulated as a second order cone programming formulation. We strengthen the new model by using perspective reformulation approach. An extensive computational study on the CAB and TR datasets demonstrates the benefits of incorporating green transportation service activities to the classic hub location problems. We also provide insights for the carrier companies by analyzing the solutions with different discount factors, service time limits and number of hubs.
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
Hierarchical multimodal hub location problem with time-definite deliveries
(Elsevier, 2012) Alumur, S. A.; Yaman, H.; Kara, B. Y.
Hierarchical multimodal hub location problem is a cost-minimizing hub covering problem where two types of hubs and hub links, accounting for ground and air transportation, are to be established, while ensuring time-definite deliveries. We propose a mixed-integer programming formulation and perform a comprehensive sensitivity analysis on the Turkish network. We show that the locations of airport hubs are less sensitive to the cost parameters compared to the locations of ground hubs and it is possible to improve the service quality at not much additional cost in the resulting multimodal networks. Our methodology provides the means for a detailed trade-off analysis.
Open Access
A hub covering network design problem for cargo applications in Turkey
(Palgrave Macmillan, 2009) Alumur, S.; Kara, B. Y.
Hub location problems involve locating hub facilities and allocating demand nodes to hubs in order to provide service between origin-destination pairs. In this study, we focus on cargo applications of the hub location problem. Through observations from the Turkish cargo sector, we propose a new mathematical model for the hub location problem that relaxes the complete hub network assumption. Our model minimizes the cost of establishing hubs and hub links, while designing a network that services each origin-destination pair within a time bound. We formulate a single-allocation hub covering model that permits visiting at most three hubs on a route. The model is then applied to the realistic instances of the Turkish network and to the Civil Aeronautics Board data set.
Open Access
Hub location and Hub network design
(2009) Alumur, Sibel Alev
he hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between origin–destination pairs. Hub location problems arise in various application settings in telecommunication and transportation. In the extensive literature on the hub location problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Throughout this thesis we relax the complete hub network assumption in hub location problems and focus on designing hub networks that are not necessarily complete. We approach to hub location problems from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub network must be designed. We focus on the single allocation version of the problems where each demand center is allocated to a single hub node. We start with introducing the 3-stop hub covering network design problem. In this problem, we aim to design hub networks so that all origin– destination pairs receive service by visiting at most three hubs on a route. Then, we include hub network design decisions in the classical hub location problems introduced in the literature. We introduce the single allocation incomplete p-hub median, hub location with fixed costs, hub covering, and p-hub center network design problems to the literature. Lastly, we introduce the multimodal hub location and hub network design problem. We include the possibility of using different hub links, and allow for different transportation modes between hubs, and for different types of service time promises between origin–destination pairs, while designing the hub network in the multimodal problem. In this problem, we jointly consider transportation costs and travel times, which are studied separately in hub location problems presented in the literature. Computational analyses with all of the proposed models are presented on the various instances of the CAB data set and on the Turkish network.
Open Access
Hub location and routing problem
(2016-01) Bayraktar, Sinan
Hubs are special facilities that consolidate and disseminate ows in many-to-many distribution systems. The hub location problem aims to nd locations of hubs and allocate non-hub nodes directly to the hubs. However, this problem is necessary to extend when nodes do not have su cient demand to justify direct connections between the non-hub nodes to the hubs since such direct connections increase the number of vehicles required and decrease the utilization of vehicles. Hence, it is necessary to construct local tours among the nodes allocated to the same hubs to generate economies of scale and to decrease vehicle costs. Nevertheless, forcing each non-hub node to be visited by a local tour is not the best way to design a many-to-many distribution system. Therefore, in this study two options for each non-hub node are given: (i) either it could be visited by a local tour or (ii) it could be directly connected to a hub without an economy of scale. We develop a mixed integer programming formulation and strengthen it with valid inequalities. We also develop three di erent Benders formulations as exact solution methods. In addition, we develop a hierarchical heuristic with two phases in order to solve large-sized problem instances. We test the performances of our solution methodologies on CAB and TR data sets.
Open Access
Hub location proplems under polyhedral demand uncertainty
(2015-07) Meraklı, Merve
Hubs are points of consolidation and transshipment in many-to-many distribution systems that bene t from economies of scale. In hub location problems, the aim is to locate hub facilities such that each pairwise demand is satis ed and the total cost is minimized. The problem usually arises in the strategic planning phase prior to observing actual demand values. Hence incorporating robustness into hub location decisions under data uncertainty is crucial for achieving a reliable hub network design. In this thesis, we study hub location problems under polyhedral demand uncertainty. We consider uncapacitated multiple allocation p-hub median problem under hose and hybrid demand uncertainty and capacitated multiple allocation hub location problem under hose demand uncertainty. We propose mixed integer linear programming formulations and devise several exact solution algorithms based on Benders decomposition in order to solve large-scale problem instances. Computational experiments are performed on instances of three benchmark data sets from the literature.
Open Access
Hub location under competition
(Elsevier, 2016) Mahmutogullari, A. I.; Kara, B. Y.
Hubs are consolidation and dissemination points in many-to-many flow networks. Hub location problem is to locate hubs among available nodes and allocate non-hub nodes to these hubs. The mainstream hub location studies focus on optimal decisions of one decision-maker with respect to some objective(s) even though the markets that benefit hubbing are oligopolies. Therefore, in this paper, we propose a competitive hub location problem where the market is assumed to be a duopoly. Two decision-makers (or firms) sequentially decide locations of their hubs and then customers choose one firm with respect to provided service levels. Each decision-maker aims to maximize his/her own market share. We propose two problems for the leader (former decision-maker) and follower (latter decision-maker): (r|Xp)hub − medianoid and (r|p)hub − centroid problems, respectively. Both problems are proven to be NP-complete. Linear programming models are presented for these problems as well as exact solution algorithms for the (r|p)hub − centroid problem. The performance of models and algorithms are tested by computational analysis conducted on CAB and TR data sets.
Open Access
Hub location under competition
(2013) Mahmutoğulları, Ali İrfan
Hubs are consolidation and dissemination points in many-to-many flow networks. The hub location problem is to locate hubs among available nodes and allocate non-hub nodes to these hubs. The mainstream hub location studies focus on optimal decisions of one decision-maker with respect to some objective(s) even though the markets that benefit hubbing are oligopolies. Therefore, in this thesis, we propose a competitive hub location problem where the market is assumed to be a duopoly. Two decision-makers (or firms) sequentially decide the locations of their hubs and then customers choose the firm according to provided service levels. Each decision-maker aims to maximize his/her market share. Having investigated the existing studies in the field of economy, retail location and operation research, we propose two problems for the leader (former decision-maker) and follower (latter decision-maker): (r|Xp) hub-medianoid and (r|p) hub-centroid problems. After defining them as combinatorial optimization problems, the problems are proved to be NP-hard. Linear programming models are presented for these problems as well as exact solution algorithms for the (r|p) hub-centroid problem that outperform the linear model in terms of memory requirement and CPU time. The performance of models and algorithms are tested by the computational analysis conducted on two well-known data sets from the hub location literature.
Open Access
Hub location, routing, and route dimensioning: strategic and tactical intermodal transportation hub network design
(Institute for Operations Research and the Management Sciences (INFORMS), 2021-10) Yıldız, Barış; Yaman, Hande; Karaşan, Oya Ekin
We propose a novel hub location model that jointly eliminates some of the traditional assumptions on the structure of the network and on the discount as a result of economies of scale in an effort to better reflect real-world logistics and transportation systems. Our model extends the hub literature in various facets: instead of connecting nonhub nodes directly to hub nodes, we consider routes with stopovers; instead of connecting pairs of hubs directly, we design routes that can visit several hub nodes; rather than dimensioning pairwise connections, we dimension routes of vehicles; and rather than working with a homogeneous fleet, we use intermodal transportation. Decisions pertinent to strategic and tactical hub location and transportation network design are concurrently made through the proposed optimization scheme. An effective branch-and-cut algorithm is developed to solve realistically sized problem instances and to provide managerial insights.
Open Access
The latest arrival hub location problem for cargo delivery systems with stopovers
(Elsevier, 2007) Yaman, H.; Kara, B. Y.; Tansel, B. C.
In this paper, we concentrate on the service structure of ground-transportation based cargo delivery companies. The transient times that arise from nonsimultaneous arrivals at hubs (typically spent for unloading, loading, and sorting operations) can constitute a significant portion of the total delivery time for cargo delivery systems. The latest arrival hub location problem is a new minimax model that focuses on the minimization of the arrival time of the last item to arrive, taking into account journey times as well as the transient times at hubs. We first focus on a typical cargo delivery firm operating in Turkey and observe that stopovers are essential components of a ground-based cargo delivery system. The existing formulations of the hub location problem in the literature do not allow stopovers since they assume direct connections between demand centers and hubs. In this paper, we propose a generic mathematical model, which allows stopovers for the latest arrival hub location problem. We improve the model using valid inequalities and lifting. We present computational results using data from the US and Turkey.