Optimal management of logistic activities in multi-site environments

The new emerging area of Enterprise Wide Optimization (EWO) has focused the attention in effectively solving the combined production/distribution scheduling problem. The importance of logistic activities performed in multi-site environments comes from the relative magnitude of the associated transportation costs and the good chance of getting large savings on such expenses. This paper first develops an exact MILP mathematical formulation for the multiple vehicle time-window-constrained pickup and delivery (MVPDPTW) problem. The approach is able to account for many-to-many transportation requests, pure pickup and delivery tasks, heterogeneous vehicles and multiple depots. Optimal solutions for a variety of benchmark problems with cluster/random distributions of pickup and delivery locations and limited sizes in terms of customer requests and vehicles have been discovered. However, the computational cost exponentially grows with the number of requests. For large-scale m-PDPTW problems, a local search improvement algorithm steadily providing a better solution through two evolutionary steps is also presented. A neighborhood structure around the starting solution is generated by first allowing multiple request exchanges among nearby trips and then permitting the reordering of nodes on every individual route. If a better set of routes is found, both steps are repeated until no improved solution is discovered. Compact MILP mathematical formulations for both sub-problems have been developed and solved through an efficient branch-and-bound algorithm. A significant number of large-scale m-PDPTW benchmark problems, some of them including up to 100 transportation requests, were successfully solved in reasonable CPU times.     

The effect of probability of coalescence on the evolution of bubble sizes in a turbulent pipeline flow: A numerical study

A population balance method in which continuum and discrete phases are integrated is developed to simulate the evolution of polydisperse population of bubbles in a turbulent pipeline flow. The investigation is focused on the effect of the coalescence efficiency on this evolution. A dilute system of bubbles under microgravity conditions is considered. It is found that if the initial coalescence efficiency is low, a slight increase produces a significant effect on the bubble coalescence rate, and thus on the evolution of the population. If, however, the initial coalescence efficiency is high, its increase results in a marginal effect on the way the population evolves. The results of simulations are validated against experimental data on the population mean.     

Karyotype description of Pomacea patula catemacensis (Caenogastropoda, Ampullariidae), with an assessment of the taxonomic status of Pomacea patula.

Mitotic chromosomes of the freshwater snail Pomacea patula catemacensis (Baker 1922) were analyzed on gill tissue of specimens from the type locality (Lake Catemaco, Mexico). The diploid number of chromosomes is 2n = 26, including nine metacentric and four submetacentric pairs; therefore, the fundamental number is FN = 52, No sex chromosomes could be identified. The same chromosome number and morphology were already reported for P. flagellata, i.e., the other species of the genus living in Mexico. The basic haploid number for family Ampullariidae was reported to be n = 14 in the literature; so, its reduction to n = 13 is probably an apomorphy of the Mexican Pomacea snails. Lanistes bolteni, from Egypt, also shows n = 13, but its karyotype is much more asymmetrical, and seems to have evolved independently from P. flagellata and P. patula catemacensis. The nominotypical subspecies, P. patula patula (Reeve 1856), is a poorly known taxon, whose original locality is unknown. A taxonomical account is presented here, and a Mexican origin postulated as the most parsimonious hypothesis.     

Introducing fuzziness in object models and database interfaces through aspects

Imperfection in information can be considered a crosscutting concern that manifests itself in diverse kinds of imprecision, uncertainty, or inconsistency in the data models of a software system. The extension of existing programming and querying interfaces for the different aspects of information imperfection requires a proper modularization of the different concerns of numerical imprecision handling, so that the extensions do not interfere with existing programming practices and do not obscure the original design. Aspect‐oriented design (AOD) enables such a form of nonintrusive extensions to be added to existing software libraries, clearly separating fuzziness or other imperfections in data as a differentiated concern that can be considered from the early phases of development. In this article, a general framework for aspect‐based extension of data models and fuzzy databases is described, and some design and implementation issues of such AOD‐based extensions on OJB database libraries are described as a case study. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1199–1216, 2006.     

An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL)

Diabetes therapy management in AAL environments, such as old people and diabetes patients homes, is a very difficult task since many factors affect a patient’s blood sugar levels. Factors such as illness, treatments, physical and psychological stress, physical activity, drugs, intravenous fluids and change in the meal plan cause unpredictable and potentially dangerous fluctuations in blood sugar levels. Right now, operations related to dosage are based on insulin infusion protocol boards, which are provided by physicians to the patients. These boards are not considering very influential factors such as glycemic index from the diet, consequently patients need to estimate the dosage leading to dose error, which culminates in hyperglycemia and hypoglycemia episode. Therefore, right insulin infusion calculation needs to be supported by the next generation of personal-care devices. For this reason, a personal device has been developed to assist and consider more factors in the insulin therapy dosage calculation. The proposed solution is based on Internet of things in order to, on the one hand, support a patient’s profile management architecture based on personal RFID cards and, on the other hand, provide global connectivity between the developed patient’s personal device based on 6LoWPAN, nurses/physicians desktop application to manage personal health cards, glycemic index information system, and patient’s web portal. This solution has been evaluated by a multidisciplinary group formed by patients, physicians, and nurses.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.     

mfERG_LAB: Software for processing multifocal electroretinography signals

The multifocal electroretinography technique consists of performing sectorized light excitation of the retina and capturing the resulting evoked potential. This provides functional localized information about the state of the retinal neurons. Analysis of multifocal electroretinography signals can be used for diagnosing different types of optic neuropathies (glaucomatous, demyelinating and ischemic ethiology). In order to obtain a reliable diagnosis, it is necessary to apply advanced processing algorithms (morphological, frequency and time-frequency analysis, etc.) to the multifocal electroretinography signal. This paper presents a software application developed in MATLAB(?) (MathWorks Inc., MA) designed to perform advanced multifocal electroretinography signal analysis and classification. This intuitive application, mfERG_LAB, is used to plot the signals, apply various algorithms to them and present the data in an appropriate format. The application's computational power and modular structure make it suitable for use in clinical settings as a powerful and innovative diagnostic tool, as well as in research and teaching settings as a means of assessing new algorithms.     

Modelling and solving English Peg Solitaire

Peg Solitaire is a well known puzzle, which can prove difficult despite its simple rules. Pegs are arranged on a board such that at least one ‘hole’ remains. By making draughts/checkers-like moves, pegs are gradually removed until no further moves are possible or some goal configuration is achieved. This paper considers the English variant, consisting of a board in a cross shape with 33 holes. Modelling Peg Solitaire via constraint or integer programming techniques presents a considerable challenge and is examined in detail. The merits of the resulting models are discussed and they are compared empirically. The sequential nature of the puzzle naturally conforms to a planning problem, hence we also present an experimental comparison with several leading AI planning systems. Other variants of the puzzle, such as ‘Fool's Solitaire’ and ‘Long-hop’ Solitaire are also considered.