Search results for: OPTIMIZATION PROBLEMS
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Algorytmy Optymalizacji Dyskretnej - ed. 2021/2022
e-Learning CoursesIn real-world applications, many important practical problems are NP-hard, therefore it is expedient to consider not only the optimal solutions of NP-hard optimization problems, but also the solutions which are “close” to them (near-optimal solutions). So, we can try to design an approximation algorithm that efficiently produces a near-optimal solution for the NP-hard problem. In many cases we can even design approximation algorithms...
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublicationIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Expedited antenna optimization with numerical derivatives and gradient change tracking
PublicationDesign automation has been playing an increasing role in the development of novel antenna structures for various applications. One of its aspects is electromagnetic (EM)-driven design closure, typically applied upon establishing the antenna topology, and aiming at adjustment of geometry parameters to boost the performance figures as much as possible. Parametric optimization is often realized using local methods given usually reasonable...
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Multimodal Particle Swarm Optimization with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublicationIn this paper, a new meta-heuristic method of finding roots and poles of a complex function of a complex variable is presented. The algorithm combines an efficient space exploration provided by the particle swarm optimization (PSO) and the classification of root and pole occurrences based on the phase analysis of the complex function. The method initially generates two uniformly distributed populations of particles on the complex...
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublicationTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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Team Strategies - sem. 2022/23
e-Learning CoursesThe main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task
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Team Strategies - sem. 2023/24
e-Learning CoursesThe main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task
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Team Strategies - sem. 2024/25
e-Learning CoursesThe main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task
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Key issues in modeling and optimization of lignocellulosic biomass fermentative conversion to gaseous biofuels
PublicationThe industrial-scale production of lignocellulosic-based biofuels from biomass is expected to benefit society and the environment. The main pathways of residues processing include advanced hydrolysis and fermentation, pyrolysis, gasification, chemical synthesis and biological processes. The products of such treatment are second generation biofuels. The degree of fermentation of organic substances depends primarily on their composition...
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Preference-based evolutionary multi-objective optimization in ship weather routing
PublicationIn evolutionary multi-objective optimization (EMO) the aim is to find a set of Pareto-optimal solutions. Such approach may be applied to multiple real-life problems, including weather routing (WR) of ships. The route should be optimal in terms of passage time, fuel consumption and safety of crew and cargo while taking into account dynamically changing weather conditions. Additionally it must not violate any navigational constraints...
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Zero-Pole Approach in Microwave Passive Circuit Design
PublicationIn this thesis, optimization strategies for design of microwave passive structures including filters, couplers, antenna and impedance transformer and construction of various surroogate models utilized to fasten the design proces have been discussed. Direct and hybrid optimization methodologies including space mapping and multilevel algorithms combined with various surrogate models at different levels of fidelity have been utilized...
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Towards solving heterogeneous fleet vehicle routing problem with time windows and additional constraints: real use case study
PublicationIn advanced logistic systems, there is a need for a comprehensive optimization of the transport of goods, which would reduce costs. During past decades, several theoretical and practical approaches to solve vehicle routing problems (VRP) were proposed. The problem of optimal fleet management is often transformed to discrete optimization problem that relies on determining the most economical transport routes for a number of vehicles...
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Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption
PublicationMany important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power of such systems requires programming parallel applications that are hybrid in two meanings: they can utilize parallelism on multiple levels at the same time and combine together programming interfaces...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublicationIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String
PublicationA new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard...
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Parallel tabu search for graph coloring problem
PublicationTabu search is a simple, yet powerful meta-heuristic based on local search that has been often used to solve combinatorial optimization problems like the graph coloring problem. This paper presents current taxonomy of patallel tabu search algorithms and compares three parallelization techniques applied to Tabucol, a sequential TS algorithm for graph coloring. The experimental results are based on graphs available from the DIMACS...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublicationPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Proximal primal–dual best approximation algorithm with memory
PublicationWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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Selected dynamic properties of adaptive proportional observer of induction motor state variables
PublicationThis paper presents problems related to the design and the stability of adaptive proportional observer which is used for estimation of magnetic flux and motor speed in sensorless control systems of induction motor. The gain matrix of the observer was chosen by genetic algorithm and alternatively by pole placement method. It has been shown that adaptive proportional observer is stable if the...
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KOALA Graph Theory Internet Service
PublicationKOALA has been created with the idea of C++ library templates, implementing a broad set of procedures in the fields of algorithmic graph theory and network problems in discreate optimization. During the C2NIWA project, a library has been greatly ectended, the code refactored and enclosed with the internet service available in the public repository of thr project. Today it contains interconnected educational materials in the form...
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Modified DNA polymerases for PCR troubleshooting
PublicationPCR has become an essential tool in biological science. However, researchers often encounter problems with difficult targets, inhibitors accompanying the samples, or PCR trouble related to DNA polymerase. Therefore, PCR optimization is necessary to obtain better results. One solution is using modified DNA polymerases with desirable properties for the experiments. In this article, PCR troubleshooting, depending on the DNA polymerase...
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Janusz Cieśliński prof. dr hab. inż.
PeopleHe was born on April 15, 1954 in Slupsk. He graduated from the Faculty of Mechanical Engineering at Gdańsk University of Technology (1978). In 1986 he received the title of Doctor, in 1997 he obtained the title of Ph.D. with habilitation, and in 2006 he received the title of Professor. He worked as head of department and vice-dean for Education at the Faculty of Mechanical Engineering for two terms (2002-2008). His research interests...
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Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
PublicationThe paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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On the low-cost design of abbreviated multisection planar matching transformer
PublicationA numerically demanding wideband matching transformer composed of three nonuniform transmission lines (NUTLs) has been designed and optimized at a low computational cost. The computational feasibility of the design has been acquired through the exploitation of low-fidelity NUTL models in most steps of the design procedure and an implicit space mapping optimization engine, providing high accuracy results with only a handful of EM...
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A decision-making system supporting selection of commanded outputs for a ship's propulsion system with a controllable pitch propeller
PublicationThe ship's operators have to make decisions regarding the values of commanded outputs (commanded engine speed and pitch ratio) which ensure maximum vessel speed and minimum fuel consumption. Obviously, the presented decision problems are opposed. Therefore, there is a need for a compromise solution that enables more flexible vessel voyage planning. This paper deals with development of a computer-aided system supporting selection...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Expedited Re-Design of Multi-Band Passive Microwave Circuits Using Orthogonal Scaling Directions and Gradient-Based Tuning
PublicationGeometry scaling of microwave circuits is an essential but challenging task. In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates utilization of numerical optimization methods. Nonetheless, if the intended frequencies are distant from the ones at the starting point,...
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Comparison of reproduction strategies in genetic algorithm approach to graph searching
Publicationgenetic algorithms (ga) are a well-known tool used to obtain approximate solutions to optimization problems. successful application of genetic algorithm in solving given problem is largely dependant on selecting appropriate genetic operators. selection, mutation and crossover techniques play a fundamental role in both time needed to obtain results and their accuracy. in this paper we focus on applying genetic algorithms in calculating...
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How can analysts use multicriteria decision analysis?
PublicationProper decision making in multifacitated situation is very challenging task. It is especially difficult if there are many alternatives and criteria that are often contradictory. Analytical chemistry and related sciences involve many situations where decisions on complex problems are made. The support tools may be the use of MCDA (Multi-criteria Decision Analysis) algorithms. They formalize the decision process, make it transparent...
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Inline Microwave Filters With N+1 Transmission Zeros Generated by Frequency-Variant Couplings: Coupling-Matrix-Based Synthesis and Design
PublicationA general coupling-matrix-based synthesis methodology for inline Nth-order microwave bandpass filters (BPFs) with frequency-variant reactive-type couplings that generate N+1 transmission zeros (TZs) is presented in this brief. The proposed approach exploits the formulation of the synthesis problem as three inverse nonlinear eigenvalue problems (INEVPs) so that the coupling matrix is built from their sets of eigenvalues. For this...
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Optymalizacja strategii sieci inteligentnych agentów za pomocą programowania genetycznego w systemie rozproszonym realizującym paradygmat volunteer computing
PublicationDynamicznie rosnąca złożoność i wymagania w odniesieniu do rozproszonych systemów informatycznych utrudnia zarządzanie dostępnymi zasobami sprzętowymi i programistycznymi. Z tego powodu celem rozprawy jest opracowanie wielokryterialnej metody programowania genetycznego, która pozwala na optymalizację strategii zespołu inteligentnych agentów programistycznych w zakresie zarządzania systemem realizującym paradygmat volunteer computing....
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DETERMINATION OF OBJECTIVES FOR URBAN FREIGHT POLICY
PublicationBackground: Decisions regarding strategic planning of urban freight transport very often are based on superficial assumptions inadequately reflecting the actual character of encountered challenges. The trend may be observed to adapt isolated solutions without supporting measures and verification of expected outcomes. Selected urban freight solutions have a significant potential to alleviate transport related problems, but they...
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Simulation-driven design of compact ultra-wideband antenna structures
PublicationPurpose–The purpose of this paper is to investigate strategies and algorithms for expedited designoptimization and explicit size reduction of compact ultra-wideband (UWB) antennas.Design/methodology/approach–Formulation of the compact antenna design problem aiming atexplicit size reduction while maintaining acceptable electrical performance is presented. Algorithmicframeworks are described suitable for handling various design situations...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublicationFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Study of a Multicriterion Decision-Making Approach to the MQL Turning of AISI 304 Steel Using Hybrid Nanocutting Fluid
PublicationThe enormous use of cutting fluid in machining leads to an increase in machining costs, along with different health hazards. Cutting fluid can be used efficiently using the MQL (minimum quantity lubrication) method, which aids in improving the machining performance. This paper contains multiple responses, namely, force, surface roughness, and temperature, so there arises a need for a multicriteria optimization technique. Therefore,...
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On Tradeoffs Between Width- and Fill-like Graph Parameters
PublicationIn this work we consider two two-criteria optimization problems: given an input graph, the goal is to find its interval (or chordal) supergraph that minimizes the number of edges and its clique number simultaneously. For the interval supergraph, the problem can be restated as simultaneous minimization of the path width pw(G) and the profile p(G) of the input graph G. We prove that for an arbitrary graph G and an integer t ∈ {1,...
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Boundary value problems for ordinary differential equations with deviated arguments
PublicationDyskutowane są równania różniczkowe z dwupunktowym nieliniowym warunkiem brzegowym z argumentami typu odchylonego. Podano warunki dostateczne które gwarantują iż problem wyjściowy ma kwazi-rozwiązania. Podano też warunki przy których problem ten ma rozwiązanie. Wyniki uzyskano stosując metodę iteracji monotonicznych.Badano też pewne nierówności różniczkowe z odchylonymi argumentami.
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Four-point boundary-value problems for differential-algebraic systems
PublicationBadane są czteropunktowe problemy brzegowe dla układów równań różniczkowo-algebraicznych. Stosując metodę iteracji monotonicznych, podano warunki dostateczne na istnienie rozwiązań (jednego lub ekstremalnych) takich problemów. Podano przykład ilustrujacy otrzymane wyniki teoretyczne.
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Prenatal exposure to substance of abuse: A worldwide problem
PublicationSubstance abuse during pregnancy is an important public health issue affecting the mother and the growing infant. Preterm labor, miscarriage, abruption and postpartum hemorrhage are obstetric complications which have been associated with women who are dependent on abused substances. Moreover, women are also at an increased risk of medical problems such as poor nutrition, anemia, urinary tract infections as well as sexually transmitted...
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Fundamentals of Physics-Based Surrogate Modeling
PublicationChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
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A 3D-FEM mesh technique for fast analysis of waveguide problems containing rotatable tuning elements
PublicationIn this paper a meshing technique for 3D Finite Element Method is presented. It allows for fast analysis and optimization of the waveguide structures, which contain rotatable tuning elements. In the proposed procedure a thin layer of varying cylindrical mesh buffer is introduced in order to reuse unchanged mesh and FEM matrices in the rest of the domain.
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Constructing a map of an anonymous graph: applications of universal sequences
PublicationWe study the problem of mapping an unknown environmentrepresented as an unlabelled undirected graph. A robot (or automaton)starting at a single vertex of the graph G has to traverse the graph and return to its starting point building a map of the graph in the process. We are interested in the cost of achieving this task (whenever possible) in terms of the number of edge traversal made by the robot. Another optimization criteria...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublicationRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Communication and Load Balancing Optimization for Finite Element Electromagnetic Simulations Using Multi-GPU Workstation
PublicationThis paper considers a method for accelerating finite-element simulations of electromagnetic problems on a workstation using graphics processing units (GPUs). The focus is on finite-element formulations using higher order elements and tetrahedral meshes that lead to sparse matrices too large to be dealt with on a typical workstation using direct methods. We discuss the problem of rapid matrix generation and assembly, as well as...
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Multiple solutions of boundary-value problems for fourth-order differential equations with deviating arguments
PublicationPraca dotyczy równań różniczkowych rzędu czwartego z warunkami brzegowymi i odchylonymi argumentami. Podano wystarczające warunki, dla których problemy dotyczące takich równań mają dodatnie rozwiązania. W pracy rozważa się przypadki kiedy argumenty odchylone są typu opóźnionego lub wyprzedzonego. W celu zapewnienia istnienia przynajmniej trzech dodatnich rozwiązań wykorzystano twierdzenie Avery-Petersona.