150 resultados para Modelos de Location-Allocation


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Previous covering models for emergency service consider all the calls to be of the sameimportance and impose the same waiting time constraints independently of the service's priority.This type of constraint is clearly inappropriate in many contexts. For example, in urban medicalemergency services, calls that involve danger to human life deserve higher priority over calls formore routine incidents. A realistic model in such a context should allow prioritizing the calls forservice.In this paper a covering model which considers different priority levels is formulated andsolved. The model heritages its formulation from previous research on Maximum CoverageModels and incorporates results from Queuing Theory, in particular Priority Queuing. Theadditional complexity incorporated in the model justifies the use of a heuristic procedure.

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The emphasis on integrated care implies new incentives that promote coordinationbetween levels of care. Considering a population as a whole, the resource allocation systemhas to adapt to this environment. This research is aimed to design a model that allows formorbidity related prospective and concurrent capitation payment. The model can be applied inpublicly funded health systems and managed competition settings.Methods: We analyze the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding total health expenditures for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2004 and2005.Results: The hybrid model reimburses integrated care organizations avoiding excessive risktransfer and maximizing incentives for efficiency in the provision. At the same time, it eliminatesincentives for risk selection for a specific set of high risk individuals through the use ofconcurrent reimbursement in order to assure a proper classification of patients.Conclusion: Prospective Risk Adjustment is used to transfer the financial risk to the healthprovider and therefore provide incentives for efficiency. Within the context of a National HealthSystem, such transfer of financial risk is illusory, and the government has to cover the deficits.Hybrid risk adjustment is useful to provide the right combination of incentive for efficiency andappropriate level of risk transfer for integrated care organizations.

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We analyze empirically the allocation of rights and monetary incentives in automobile franchise contracts. These contracts substantially restrict the decision rights of dealers and grant manufacturers extensive contractual completion and enforcement powers, converting the manufacturers, de facto, in a sort of quasi-judiciary instance. Variation in the allocation of decision rights andincentive intensity is explained by the incidence of moral hazard in the relation. In particular, when the cost of dealer moral hazard is higher and the risk of manufactureropportunism is lower, manufacturers enjoy more discretion in determining the performance required from their dealers and in using mechanisms such as monitoring, termination and monetary incentives to ensure such performance is provided. We also explore the existence of interdependencies between the different elements of the system. and find some complementarities between completion and termination rights, and between monitoring rights and the intensity of incentives.

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The earning structure in science is known to be flat relative to the one in theprivate sector, which could cause a brain drain toward the private sector. In thispaper, we assume that agents value both money and fame and study the role ofthe institution of science in the allocation of talent between the science sector andthe private sector. Following works on the Sociology of Science, we model theinstitution of science as a mechanism distributing fame (i.e. peer recognition). Weshow that since the intrinsic performance is less noisy signal of talent in the sciencesector than in the private sector, a good institution of science can mitigate thebrain drain. We also find that providing extra monetary incentives through themarket might undermine the incentives provided by the institution and therebyworsen the brain drain. Finally, we study the optimal balance between monetaryand non-monetary incentives in science.

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This article studies the effects of interest rate restrictions on loan allocation. The British governmenttightened the usury laws in 1714, reducing the maximum permissible interest rate from 6% to5%. A sample of individual loan transactions reveals that average loan size and minimum loan sizeincreased strongly, while access to credit worsened for those with little social capital. Collateralisedcredits, which had accounted for a declining share of total lending, returned to their former role ofprominence. Our results suggest that the usury laws distorted credit markets significantly; we findno evidence that they offered a form of Pareto-improving social insurance.

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The paper presents a new model based on the basic Maximum Capture model,MAXCAP. The New Chance Constrained Maximum Capture modelintroduces astochastic threshold constraint, which recognises the fact that a facilitycan be open only if a minimum level of demand is captured. A metaheuristicbased on MAX MIN ANT system and TABU search procedure is presented tosolve the model. This is the first time that the MAX MIN ANT system isadapted to solve a location problem. Computational experience and anapplication to 55 node network are also presented.

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A new direction of research in Competitive Location theory incorporatestheories of Consumer Choice Behavior in its models. Following thisdirection, this paper studies the importance of consumer behavior withrespect to distance or transportation costs in the optimality oflocations obtained by traditional Competitive Location models. To dothis, it considers different ways of defining a key parameter in thebasic Maximum Capture model (MAXCAP). This parameter will reflectvarious ways of taking into account distance based on several ConsumerChoice Behavior theories. The optimal locations and the deviation indemand captured when the optimal locations of the other models are usedinstead of the true ones, are computed for each model. A metaheuristicbased on GRASP and Tabu search procedure is presented to solve all themodels. Computational experience and an application to 55-node networkare also presented.

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In this paper we propose a metaheuristic to solve a new version of the Maximum CaptureProblem. In the original MCP, market capture is obtained by lower traveling distances or lowertraveling time, in this new version not only the traveling time but also the waiting time willaffect the market share. This problem is hard to solve using standard optimization techniques.Metaheuristics are shown to offer accurate results within acceptable computing times.

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New location models are presented here for exploring the reduction of facilities in aregion. The first of these models considers firms ceding market share to competitorsunder situations of financial exigency. The goal of this model is to cede the leastmarket share, i.e., retain as much of the customer base as possible while sheddingcostly outlets. The second model considers a firm essentially without competition thatmust shrink it services for economic reasons. This firm is assumed to close outlets sothat the degradation of service is limited. An example is offered within a competitiveenvironment to demonstrate the usefulness of this modeling approach.

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The goal of this paper is to present an optimal resource allocation model for the regional allocation of public service inputs. Theproposed solution leads to maximise the relative public service availability in regions located below the best availability frontier, subject to exogenous budget restrictions and equality ofaccess for equal need criteria (equity-based notion of regional needs). The construction of non-parametric deficit indicators is proposed for public service availability by a novel application of Data Envelopment Analysis (DEA) models, whose results offer advantages for the evaluation and improvement of decentralised public resource allocation systems. The method introduced in this paper has relevance as a resource allocation guide for the majority of services centrally funded by the public sector in a given country, such as health care, basic and higher education, citizen safety, justice, transportation, environmental protection, leisure, culture, housing and city planning, etc.

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We postulate a two-region world, comprised of North (calibrated after the US) and South(calibrated after China). Our optimization results show the compatibility of the following threedesiderata:(1) Global CO2 emissions follow a conservative path that leads to the stabilizationof concentrations at 450 ppm.(2) North and South converge to a path of sustained growth at 1% per year (28.2%per generation) in 2075.(3) During the transition to the steady state, North also grows at 1% per year whileSouth s rates of growth are markedly higher.The transition paths require a drastic reduction of the share of emissions allocated to North,large investments in knowledge, both in North and South, as well as very large investments ineducation in South. Surprisingly, in order to sustain North s utility growth rate, some output mustbe transferred from South to North during the transition.Although undoubtedly subject to many caveats, our results support a degree of optimism byproviding prima facie evidence of the possibility of tackling climate change in a way that is fairboth across generations and across regions while allowing for positive rates of humandevelopment.

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Models are presented for the optimal location of hubs in airline networks, that take into consideration the congestion effects. Hubs, which are the most congested airports, are modeled as M/D/c queuing systems, that is, Poisson arrivals, deterministic service time, and {\em c} servers. A formula is derived for the probability of a number of customers in the system, which is later used to propose a probabilistic constraint. This constraint limits the probability of {\em b} airplanes in queue, to be lesser than a value $\alpha$. Due to the computational complexity of the formulation. The model is solved using a meta-heuristic based on tabu search. Computational experience is presented.

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We propose a model and solution methods, for locating a fixed number ofmultiple-server, congestible common service centers or congestible publicfacilities. Locations are chosen so to minimize consumers congestion (orqueuing) and travel costs, considering that all the demand must be served.Customers choose the facilities to which they travel in order to receiveservice at minimum travel and congestion cost. As a proxy for thiscriterion, total travel and waiting costs are minimized. The travel costis a general function of the origin and destination of the demand, whilethe congestion cost is a general function of the number of customers inqueue at the facilities.

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The results of the application of the geophysical electromagnetic prospection methods in the resolution of the problems of the spatial location of the travertine quaternary formations of the Banyoles depression are presented

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This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network