Semigroup analysis of structured populations with distributed states-at-birth arising in mathematical aquaculture

Motivated by the modelling of structured parasite populations in aquaculture we consider a class of physiologically structured population models, where individuals may be recruited into the population at different sizes in general. That is, we consider a size-structured population model with distributed states-at-birth. The mathematical model which describes the evolution of such a population is a first order nonlinear partial integro-differential equation of hyperbolic type. First, we use positive perturbation arguments and utilise results from the spectral theory of semigroups to establish conditions for the existence of a positive equilibrium solution of our model. Then we formulate conditions that guarantee that the linearised system is governed by a positive quasicontraction semigroup on the biologically relevant state space. We also show that the governing linear semigroup is eventually compact, hence growth properties of the semigroup are determined by the spectrum of its generator. In case of a separable fertility function we deduce a characteristic equation and investigate the stability of equilibrium solutions in the general case using positive perturbation arguments.

The analysis of approximate quickselect and related problems

Approximate Quickselect, a simple modification of the well known Quickselect algorithm for selection, can be used to efficiently find an element with rank k in a given range [i..j], out of n given elements. We study basic cost measures of Approximate Quickselect by computing exact and asymptotic results for the expected number of passes, comparisons and data moves during the execution of this algorithm. The key element appearing in the analysis of Approximate Quickselect is a trivariate recurrence that we solve in full generality. The general solution of the recurrence proves to be very useful, as it allows us to tackle several related problems, besides the analysis that originally motivated us. In particular, we have been able to carry out a precise analysis of the expected number of moves of the ith element when selecting the jth smallest element with standard Quickselect, where we are able to give both exact and asymptotic results. Moreover, we can apply our general results to obtain exact and asymptotic results for several parameters in binary search trees, namely the expected number of common ancestors of the nodes with rank i and j, the expected size of the subtree rooted at the least common ancestor of the nodes with rank i and j, and the expected distance between the nodes of ranks i and j.

Application of the combined integral method to Stefan problems

In this paper we present a new, accurate form of the heat balance integral method, termed the Combined Integral Method (or CIM). The application of this method to Stefan problems is discussed. For simple test cases the results are compared with exact and asymptotic limits. In particular, it is shown that the CIM is more accurate than the second order, large Stefan number, perturbation solution for a wide range of Stefan numbers. In the initial examples it is shown that the CIM reduces the standard problem, consisting of a PDE defined over a domain specified by an ODE, to the solution of one or two algebraic equations. The latter examples, where the boundary temperature varies with time, reduce to a set of three first order ODEs.

Analysis and Design of a secure WLAN solution for Cobre Las Cruces

Cobre Las Cruces is a renowned copper mining company located in Sevilla, with unexpected problems in wireless communications that have a direct affectation in production. Therefore, the main goals are to improve the WiFi infrastructure, to secure it and to detect and prevent from attacks and from the installation of rogue (and non-authorized) APs. All of that integrated with the current ICT infrastructure.This project has been divided into four phases, although only two of them have been included into the TFC; they are the analysis of the current situation and the design of a WLAN solution.Once the analysis part was finished, some weaknesses were detected. Subjects such as lack of connectivity and control, ignorance about installed WiFi devices and their localization and state and, by and large, the use of weak security mechanisms were some of the problems found. Additionally, due to the fact that the working area became larger and new WiFi infrastructures were added, the first phase took more time than expected.As a result of the detailed analysis, some goals were defined to solve and it was designed a centralized approach able to cope with them. A solution based on 802.11i and 802.1x protocols, digital certificates, a probe system running as IDS/IPS and ligthweight APs in conjunction with a Wireless LAN Controller are the main features.

Exact long-time behavior of a network of oscillators under random fields

We present an exact solution for the order parameters that characterize the stationary behavior of a population of Kuramotos phase oscillators under random external fields [Y. Kuramoto, in International Symposium on Mathematical Problems in Theoretical Physics, Lecture Notes in Physics, Vol. 39 (Springer, Berlin, 1975), p. 420]. From these results it is possible to generate the phase diagram of models with an arbitrary distribution of random frequencies and random fields.

¿Para qué sirven los problemas en la clase de matemáticas? = What is the use of problems in Mathematics lessons?

The results obtained in several yield tests, at an international level (mainly the famous PISA 2003 report, by the OCDE), have raised a multiplicity of performances in order to improve the students' yield regarding problem solving. In this article we set a clear guideline on how problems should be used in Mathematics lessons, not for obtaining better scores in the yield tests but for improving the development of Mathematical thinking in students. From this perspective, the author analyses, through eight reflections, how the concept of problem, transmitted both in the school and from society, influences the students

Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.

Be-Fe coupled method for the analysis of 3D elastodynamic problems in the time domain

By coupling the Boundary Element Method (BEM) and the Finite Element Method (FEM) an algorithm that combines the advantages of both numerical processes is developed. The main aim of the work concerns the time domain analysis of general three-dimensional wave propagation problems in elastic media. In addition, mathematical and numerical aspects of the related BE-, FE- and BE/FE-formulations are discussed. The coupling algorithm allows investigations of elastodynamic problems with a BE- and a FE-subdomain. In order to observe the performance of the coupling algorithm two problems are solved and their results compared to other numerical solutions.

Heat Source Estimation with the Conjugate Gradient Method in Inverse Linear Diffusive Problems

In this work, we present the solution of a class of linear inverse heat conduction problems for the estimation of unknown heat source terms, with no prior information of the functional forms of timewise and spatial dependence of the source strength, using the conjugate gradient method with an adjoint problem. After describing the mathematical formulation of a general direct problem and the procedure for the solution of the inverse problem, we show applications to three transient heat transfer problems: a one-dimensional cylindrical problem; a two-dimensional cylindrical problem; and a one-dimensional problem with two plates.

Simulation of Steady-State Nonlinear Heat Transfer Problems Through the Minimization of Quadratic Functionals

In this work it is presented a systematic procedure for constructing the solution of a large class of nonlinear conduction heat transfer problems through the minimization of quadratic functionals like the ones usually employed for linear descriptions. The proposed procedure gives rise to an efficient and easy way for carrying out numerical simulations of nonlinear heat transfer problems by means of finite elements. To illustrate the procedure a particular problem is simulated by means of a finite element approximation.

Datenherrschaft – an Ethically Justified Solution to the Problem of Ownership of Patient Information

Patient information systems are crucial components for the modern healthcare and medicine. It is obvious that without them the healthcare cannot function properly – one can try to imagine how brain surgery could be done without using information systems to gather and show information needed for an operation. Thus, it can be stated that digital information is irremovable part of modern healthcare. However, the legal ownership of patient information lacks a coherent and justified basis. The whole issue itself is actually bypassed by controlling pa- tient information with different laws and regulations how patient information can be used and by whom. Nonetheless, the issue itself – who owns the patient in- formation – is commonly missed or bypassed. This dissertation show the problems if the legislation of patient information ownership is not clear. Without clear legislation, the outcome can be unexpected like it seems to be in Finland, Sweden and United Kingdom: the lack of clear regulation has come up with unwanted consequences because of problematic Eu- ropean Union database directive implementation in those countries. The legal ownership is actually granted to the creators of databases which contains the pa- tient information, and this is not a desirable situation. In healthcare and medicine, we are dealing with issues such as life, health and information which are very sensitive and in many cases very personal. Thus, this dissertation leans on four philosophical theories form Locke, Kant, Heidegger and Rawls to have an ethically justified basis for regulating the patient infor- mation in a proper way. Because of the problems of property and ownership in the context of information, a new concept is needed and presented to replace the concept of owning, that concept being Datenherrschaft (eng. mastery over in- formation). Datenherrschaft seems to be suitable for regulating patient infor- mation because its core is the protection of one’s right over information and this aligns with the work of the philosophers whose theories are used in the work. The philosophical argumentation of this study shows that Datenherrschaft granted to the patients is ethically acceptable. It supports the view that patient should be controlling the patient information about themselves unless there are such specific circumstance that justifies the authorities to use patient information to protect other people’s basic rights. Thus, if the patients would be legally grant- ed Datenherrschaft over patient information we would endorse patients as indi- viduals who have their own and personal experience of their own life and have a strong stance against any unjustified paternalism in healthcare. Keywords: patient information, ownership, Datenherrschaft, ethics, Locke, Kant, Heidegger, Rawls

Meta-heuristic Solution Methods for Rich Vehicle Routing Problems

Le problème de tournées de véhicules (VRP), introduit par Dantzig and Ramser en 1959, est devenu l'un des problèmes les plus étudiés en recherche opérationnelle, et ce, en raison de son intérêt méthodologique et de ses retombées pratiques dans de nombreux domaines tels que le transport, la logistique, les télécommunications et la production. L'objectif général du VRP est d'optimiser l'utilisation des ressources de transport afin de répondre aux besoins des clients tout en respectant les contraintes découlant des exigences du contexte d’application. Les applications réelles du VRP doivent tenir compte d’une grande variété de contraintes et plus ces contraintes sont nombreuse, plus le problème est difficile à résoudre. Les VRPs qui tiennent compte de l’ensemble de ces contraintes rencontrées en pratique et qui se rapprochent des applications réelles forment la classe des problèmes ‘riches’ de tournées de véhicules. Résoudre ces problèmes de manière efficiente pose des défis considérables pour la communauté de chercheurs qui se penchent sur les VRPs. Cette thèse, composée de deux parties, explore certaines extensions du VRP vers ces problèmes. La première partie de cette thèse porte sur le VRP périodique avec des contraintes de fenêtres de temps (PVRPTW). Celui-ci est une extension du VRP classique avec fenêtres de temps (VRPTW) puisqu’il considère un horizon de planification de plusieurs jours pendant lesquels les clients n'ont généralement pas besoin d’être desservi à tous les jours, mais plutôt peuvent être visités selon un certain nombre de combinaisons possibles de jours de livraison. Cette généralisation étend l'éventail d'applications de ce problème à diverses activités de distributions commerciales, telle la collecte des déchets, le balayage des rues, la distribution de produits alimentaires, la livraison du courrier, etc. La principale contribution scientifique de la première partie de cette thèse est le développement d'une méta-heuristique hybride dans la quelle un ensemble de procédures de recherche locales et de méta-heuristiques basées sur les principes de voisinages coopèrent avec un algorithme génétique afin d’améliorer la qualité des solutions et de promouvoir la diversité de la population. Les résultats obtenus montrent que la méthode proposée est très performante et donne de nouvelles meilleures solutions pour certains grands exemplaires du problème. La deuxième partie de cette étude a pour but de présenter, modéliser et résoudre deux problèmes riches de tournées de véhicules, qui sont des extensions du VRPTW en ce sens qu'ils incluent des demandes dépendantes du temps de ramassage et de livraison avec des restrictions au niveau de la synchronization temporelle. Ces problèmes sont connus respectivement sous le nom de Time-dependent Multi-zone Multi-Trip Vehicle Routing Problem with Time Windows (TMZT-VRPTW) et de Multi-zone Mult-Trip Pickup and Delivery Problem with Time Windows and Synchronization (MZT-PDTWS). Ces deux problèmes proviennent de la planification des opérations de systèmes logistiques urbains à deux niveaux. La difficulté de ces problèmes réside dans la manipulation de deux ensembles entrelacés de décisions: la composante des tournées de véhicules qui vise à déterminer les séquences de clients visités par chaque véhicule, et la composante de planification qui vise à faciliter l'arrivée des véhicules selon des restrictions au niveau de la synchronisation temporelle. Auparavant, ces questions ont été abordées séparément. La combinaison de ces types de décisions dans une seule formulation mathématique et dans une même méthode de résolution devrait donc donner de meilleurs résultats que de considérer ces décisions séparément. Dans cette étude, nous proposons des solutions heuristiques qui tiennent compte de ces deux types de décisions simultanément, et ce, d'une manière complète et efficace. Les résultats de tests expérimentaux confirment la performance de la méthode proposée lorsqu’on la compare aux autres méthodes présentées dans la littérature. En effet, la méthode développée propose des solutions nécessitant moins de véhicules et engendrant de moindres frais de déplacement pour effectuer efficacement la même quantité de travail. Dans le contexte des systèmes logistiques urbains, nos résultats impliquent une réduction de la présence de véhicules dans les rues de la ville et, par conséquent, de leur impact négatif sur la congestion et sur l’environnement.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Anisotropic adaptive resolution of boundary layers for heat conduction problems

We deal with the numerical solution of heat conduction problems featuring steep gradients. In order to solve the associated partial differential equation a finite volume technique is used and unstructured grids are employed. A discrete maximum principle for triangulations of a Delaunay type is developed. To capture thin boundary layers incorporating steep gradients an anisotropic mesh adaptation technique is implemented. Computational tests are performed for an academic problem where the exact solution is known as well as for a real world problem of a computer simulation of the thermoregulation of premature infants.