152 research outputs found

    A new approximation algorithm for the multilevel facility location problem

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    In this paper we propose a new integer programming formulation for the multi-level facility location problem and a novel 3-approximation algorithm based on LP rounding. The linear program we are using has a polynomial number of variables and constraints, being thus more efficient than the one commonly used in the approximation algorithms for this type of problems

    A simple derivation of the waiting time distributions in a non-preemptive M/M/c queue with priorities

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    In this article we give a new derivation for the waiting time distributions in an M=M=c queue with multiple priorities and a common service rate by using elementary lattice paths counting. An advantage of the approach is that it does not require inversion of the Laplace-Stieltjes transform

    The cost-effectiveness of banning highly hazardous pesticides to prevent suicides due to pesticide self-ingestion across 14 countries:a model-based economic evaluation

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    Background: Reducing suicides is a key Sustainable Development Goal target for improving global health. Highly hazardous pesticides are among the leading causes of death by suicide in low-income and middle-income countries. National bans of acutely toxic highly hazardous pesticides have led to substantial reductions in pesticide-attributable suicides across several countries. This study evaluated the cost-effectiveness of implementing national bans of highly hazardous pesticides to reduce the burden of pesticide suicides.Methods: A Markov model was developed to examine the costs and health effects of implementing a national ban of highly hazardous pesticides to prevent suicides due to pesticide self-poisoning, compared with a null comparator. We used WHO cost-effectiveness and strategic planning (WHO-CHOICE) methods to estimate pesticide-attributable suicide rates for 100 years from 2017. Country-specific costs were obtained from the WHO-CHOICE database and denominated in 2017 international dollars (I),discountedata3), discounted at a 3% annual rate, and health effects were measured in healthy life-years gained (HLYGs). We used a demographic projection model beginning with the country population in the baseline year (2017), split by 1-year age group and sex. Country-specific data on overall suicide rates were obtained for 2017 by age and sex from the Global Burden of Disease Study 2017 Data Resources. The analysis involved 14 countries spanning low-income to high-income settings, and cost-effectiveness ratios were analysed at the country-specific level and aggregated according to country income group and the proportion of suicides due to pesticides.Findings: Banning highly hazardous pesticides across the 14 countries studied could result in about 28 000 (95% uncertainty interval [UI] 24 000–32 000) fewer suicide deaths each year at an annual cost of I0·007 per capita (95% UI 0·006–0·008). In the population-standardised results for the base case analysis, national bans produced cost-effectiveness ratios of 94perHLYG(9594 per HLYG (95% UI 73–123) across low-income and lower-middle-income countries and 237 per HLYG (95% UI 191–303) across upper-middle-income and high-income countries. Bans were more cost-effective in countries where a high proportion of suicides are attributable to pesticide self-poisoning, reaching a cost-effectiveness ratio of $75 per HLYG (95% UI 58–99) in two countries with proportions of more than 30%.Interpretation: National bans of highly hazardous pesticides are a potentially cost-effective and affordable intervention for reducing suicide deaths in countries with a high burden of suicides attributable to pesticides. However, our study findings are limited by imperfect data and assumptions that could be improved upon by future studies.Funding: WHO

    Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

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    The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a
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