Economic Lot-Sizing Problem with Bounded Inventory and Lost-Sales

In this paper we consider an economic lot-sizing problem with bounded inventory and lost-sales. Different structural properties are characterized based on the system parameters such as production and inventory costs, selling prices, and storage capacities. Using these properties and the results on the lot-sizing problems with bounded inventory, we present improved and new algorithms for the problem. Specifically, we provide algorithms for the general lot-sizing problem with bounded inventory and lost-sales, the lot-sizing problem with nonincreasing selling prices and the problem with only lost-sales

Improved Algorithms for a Lot-Sizing Problem with Inventory Bounds and Backlogging

This paper considers a dynamic lot-sizing problem with storage capacity limitation in which backlogging is allowed. For general concave production and inventory costs, we present an O(T2) dynamic programming algorithm where T is the length of the planning horizon. Furthermore, for fixed-charge and nonspeculative costs, we provide O(Tlog T) and O(T) algorithms, respectively. This paper therefore concludes that the time complexity to solve the bounded inventory lot-sizing problem with backlogging is the same as the complexity to solve the uncapacitated lot-sizing problem for the commonly used cost structure

Note on "An efficient approach for solving the lot-sizing problem with time-varying storage capacities"

In a recent paper Gutiérrez et al. (2008) show that the lot-sizing problem with inventory bounds can be solved in O(T log T) time. In this note we show that their algorithm does not lead to an optimal solution in general

Penalized composite link models for aggregated spatial count data: A mixed model approach

Mortality data provide valuable information for the study of the spatial distribution of mortality risk, in disciplines such as spatial epidemiology and public health. However, they are frequently available in an aggregated form over irregular geographical units, hindering the visualization of the underlying mortality risk. Also, it can be of interest to obtain mortality risk estimates on a finer spatial resolution, such that they can be linked to potential risk factors that are usually measured in a different spatial resolution. In this paper, we propose the use of the penalized composite link model and its mixed model representation. This model considers the nature of mortality rates by incorporating the population size at the finest resolution, and allows the creation of mortality maps at a finer scale, thus reducing the visual bias resulting from the spatial aggregation within original units. We also extend the model by considering individual random effects at the aggregated scale, in order to take into account the overdispersion. We illustrate our novel proposal using two datasets: female deaths by lung cancer in Indiana, USA, and male lip cancer incidence in Scotland counties. We also compare the performance of our proposal with the area-to-point Poisson kriging approach.We would like to thank two reviewers and an associate editor for their constructive comments and suggestions on the original manuscript. We also thank Dr. Pierre Goovaerts, who provided the high resolution population estimates described in Section 3.1. This research was supported by the Spanish Ministry of Economy and Competitiveness grants MTM2011-28285-C02-02 and MTM2014-52184-P. The research of Dae-Jin Lee was also supported by the Basque Government through the BERC 2014-2017 and ELKARTEK programs and by the Spanish Ministry of Economy and Competitiveness MINECO: BCAM Severo Ochoa excellence accreditation SEV-2013-0323. The research of Paul H. C. Eilers was also supported by the Universidad Carlos III de Madrid-Banco Santander Chair of Excellence program

Fast smoothing parameter separation in multidimensional generalized P-splines: the SAP algorithm

A new computational algorithm for estimating the smoothing parameters of a multidimensional penalized spline generalized linear model with anisotropic penalty is presented. This new proposal is based on the mixed model representation of a multidimensional P-spline, in which the smoothing parameter for each covariate is expressed in terms of variance components. On the basis of penalized quasi-likelihood methods, closed-form expressions for the estimates of the variance components are obtained. This formulation leads to an efficient implementation that considerably reduces the computational burden. The proposed algorithm can be seen as a generalization of the algorithm by Schall (1991)-for variance components estimation-to deal with non-standard structures of the covariance matrix of the random effects. The practical performance of the proposed algorithm is evaluated by means of simulations, and comparisons with alternative methods are made on the basis of the mean square error criterion and the computing time. Finally, we illustrate our proposal with the analysis of two real datasets: a two dimensional example of historical records of monthly precipitation data in USA and a three dimensional one of mortality data from respiratory disease according to the age at death, the year of death and the month of death.The authors would like to express their gratitude for the support received in the form of the Spanish Ministry of Economy and Competitiveness grants MTM2011-28285-C02-01 and MTM2011-28285-C02-02. The research of Dae-Jin Lee was funded by an NIH grant for the Superfund Metal Mixtures, Biomarkers and Neurodevelopment project 1PA2ES016454-01A2

New free-air and Bouguer gravity fields of Taiwan from multiple platforms and sensors

We construct 1' × 1' grids of free-air and Bouguer gravity anomalies around Taiwan with well-defined error estimates for quality assessment. The grids are compiled from land, airborne and shipborne gravity measurements, augmented with altimeter gravity at sea. Three sets of relative land gravity measurements are network-adjusted and outlier-edited, yielding accuracies of 0.03–0.09 mGal. Three airborne gravity sets are collected at altitudes 5156 and 1620 m with accuracies of 2.57–2.79 mGal. Seven offshore shipborne gravity campaigns around Taiwan and its offshore islands yield shallow-water gravity values with 0.88–2.35 mGal accuracies. All data points are registered with GPS-derived geodetic coordinates at cm–dm accuracies, allowing for precise gravity reductions and computing gravity disturbances. The various datasets are combined by the band-limited least-squares collocation in a one-step procedure. In the eastern mountainous (or offshore) region, Bouguer anomalies and density contrasts without considering the oceanic (or land) topographic contribution are underestimated. The new grids show unprecedented tectonic features that can revise earlier results, and can be used in a broad range of applications

A Hybrid Monte Carlo Method for Surface Growth Simulations

We introduce an algorithm for treating growth on surfaces which combines important features of continuum methods (such as the level-set method) and Kinetic Monte Carlo (KMC) simulations. We treat the motion of adatoms in continuum theory, but attach them to islands one atom at a time. The technique is borrowed from the Dielectric Breakdown Model. Our method allows us to give a realistic account of fluctuations in island shape, which is lacking in deterministic continuum treatments and which is an important physical effect. Our method should be most important for problems close to equilibrium where KMC becomes impractically slow.Comment: 4 pages, 5 figure

Escalated regeneration in sciatic nerve crush injury by the combined therapy of human amniotic fluid mesenchymal stem cells and fermented soybean extracts, Natto

Attenuation of inflammatory cell deposits and associated cytokines prevented the apoptosis of transplanted stem cells in a sciatic nerve crush injury model. Suppression of inflammatory cytokines by fermented soybean extracts (Natto) was also beneficial to nerve regeneration. In this study, the effect of Natto on transplanted human amniotic fluid mesenchymal stem cells (AFS) was evaluated. Peripheral nerve injury was induced in SD rats by crushing a sciatic nerve using a vessel clamp. Animals were categorized into four groups: Group I: no treatment; Group II: fed with Natto (16 mg/day for 7 consecutive days); Group III: AFS embedded in fibrin glue; Group IV: Combination of group II and III therapy. Transplanted AFS and Schwann cell apoptosis, inflammatory cell deposits and associated cytokines, motor function, and nerve regeneration were evaluated 7 or 28 days after injury. The deterioration of neurological function was attenuated by AFS, Natto, or the combined therapy. The combined therapy caused the most significantly beneficial effects. Administration of Natto suppressed the inflammatory responses and correlated with decreased AFS and Schwann cell apoptosis. The decreased AFS apoptosis was in line with neurological improvement such as expression of early regeneration marker of neurofilament and late markers of S-100 and decreased vacuole formation. Administration of either AFS, or Natto, or combined therapy augmented the nerve regeneration. In conclusion, administration of Natto may rescue the AFS and Schwann cells from apoptosis by suppressing the macrophage deposits, associated inflammatory cytokines, and fibrin deposits

Data-Enhanced Modeling of Sea and Swell on the Continental Shelf

LONG-TERM GOAL: Our long-term goal is to contribute to the accurate prediction of surface gravity wave generation, propagation, and dissipation in coastal regions through the combined use of measurements and models.Award #s: N00014-98-1-0019; N0001499WX30036; N0001499WR3000

Measurement of the π−\pi^- decay width of Λ5^5_\LambdaHe

We have precisely measured $\Lambda \to p\pi^-$ decay width of \5LHe and demonstrated significantly larger $\alpha$ -$\Lambda$ overlap than expected from the central repulsion $\alpha$-$\Lambda$ potential, which is derived from YNG \Lambda$-nucleon interaction.Comment: 4 pages, 3 figure