Browsing by Author "Serra, D"

Now showing 1 - 5 of 5
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    Hierarchical location-allocation models for congested systems
    (ELSEVIER SCIENCE BV, 2001) Marianov, V; Serra, D
    In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and their locations that will cover a given region with a distance or time standard. The second model is cast as a maximal covering location (MCL) formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered. (C) 2001 Elsevier Science B.V. All rights reserved.
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    Location models for airline hubs behaving as M/D/c queues
    (PERGAMON-ELSEVIER SCIENCE LTD, 2003) Marianov, V; Serra, D
    Models are presented for the optimal location of hubs in airline networks, which take into consideration the congestion effects. Hubs, which are typically the most congested airports, are modeled as M/D/c queuing systems. A formula is derived for the probability of a number of customers in the system, which is later used to propose a capacity constraint. This constraint limits the probability of more than b airplanes in queue, to be smaller than or equal to a given value. Due to the computational complexity of the formulation, the model is solved using a heuristic based on tabu search. Computational experience is presented together with an example using a data set available in the literature.
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    Location of hubs in a competitive environment
    (ELSEVIER SCIENCE BV, 1999) Marianov, V; Serra, D; ReVelle, C
    We offer a formulation that locates hubs on a network in a competitive environment; that is, customer capture is sought, which happens whenever the location of a new hub results in a reduction of the current cost (time, distance) needed by the traffic that goes from the specified origin to the specified destination. The formulation presented here reduces the number of variables and constraints as compared to existing covering models. This model is suited for both air passenger and cargo transportation. In this model, each origin-destination flow can go through either one or two hubs, and each demand point can be assigned to more than a hub, depending on the different destinations of its traffic. Links ("spokes") have no capacity limit. Computational experience is provided. (C) 1999 Elsevier Science B.V. AU rights reserved.
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    Location-allocation of multiple-server service centers with constrained queues or waiting times
    (KLUWER ACADEMIC PUBL, 2002) Marianov, V; Serra, D
    Recently, the authors have formulated new models for the location of congested facilities, so to maximize population covered by service with short queues or waiting time. In this paper, we present an extension of these models, which seeks to cover all population and includes server allocation to the facilities. This new model is intended for the design of service networks, including health and EMS services, banking or distributed ticket-selling services. As opposed to the previous Maximal Covering model, the model presented here is a Set Covering formulation, which locates the least number of facilities and allocates the minimum number of servers (clerks, tellers, machines) to them, so to minimize queuing effects. For a better understanding, a first model is presented, in which the number of servers allocated to each facility is fixed. We then formulate a Location Set Covering model with a variable (optimal) number of servers per service center (or facility). A new heuristic, with good performance on a 55-node network, is developed and tested.
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    Probabilistic, maximal covering location-allocation models for congested systems
    (BLACKWELL PUBLISHERS, 1998) Marianov, V; Serra, D
    When dealing with the design of service networks, such as health and emergency medical services, banking or distributed ticket-selling services, the location of service centers has a strong influence on the congestion at each of them, and, consequently, on the quality of service. In this paper, several probabilistic maximal covering location-allocation models with constrained waiting time for queue length are presented to consider service congestion. The first model considers the location of a given number of single-server centers such that the maximum population is served within a standard distance, and nobody stands in line for longer than a given time or with more than a predetermined number of other users. Several maximal coverage models are then formulated with one or more servers per service center. A new heuristic is developed to solve the models and tested in a 30-node network.