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Wyniki wyszukiwania dla: MULTI-OBJECTIVE QUANTUM-INSPIRED SEAGULL OPTIMIZATION ALGORITHM
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Arterial cannula shape optimization by means of the rotational firefly algorithm
PublikacjaThe article presents global optimization results of arterial cannula shapes by means of the newly modified firefly algorithm. The search for the optimal arterial cannula shape is necessary in order to minimize losses and prepare the flow that leaves the circulatory support system of a ventricle (i.e. blood pump) before it reaches the heart. A modification of the standard firefly algorithm, the so-called rotational firefly algorithm,...
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Point cloud unification with optimization algorithm
PublikacjaTerrestrial laser scanning is a technology that enables to obtain three-dimensional data – an accurate representation of reality. During scanning not only desired objects are measured, but also a lot of additional elements. Therefore, unnecessary data is being removed, what has an impact on efficiency of point cloud processing. It can happen while single point clouds are displayed – user decides what he wants...
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Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching
PublikacjaFinding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective...
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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublikacjaDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublikacjaThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Multi-Objective Water Distribution Systems Control of Pumping Cost, Water Quality, and Storage-Reliability Constraints
PublikacjaThis work describes a multi-objective model for trading-off pumping cost and water quality for water distribution systems operation. Constraints are imposed on flows and pressures, on periodical tanks operation, and on tanks storage. The methodology links the multi-objective SPEA2 algorithm with EPANET, and is applied on two example applications of increasing complexity, under extended period simulation conditions and variable...
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublikacjaIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublikacjaAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Efficient Gradient-Based Algorithm with Numerical Derivatives for Expedited Optimization of Multi-Parameter Miniaturized Impedance Matching Transformers
PublikacjaFull-wave electromagnetic (EM) simulation tools have become ubiquitous in the design of microwave components. In some cases, e.g., miniaturized microstrip components, EM analysis is mandatory due to considera¬ble cross-coupling effects that cannot be accounted for otherwise (e.g., by means of equivalent circuits). These effects are particularly pronounced in the structures in¬volving slow-wave compact cells and their numerical...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublikacjaThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Multi-objective weather routing of sailboats considering wave resistance
PublikacjaThe article presents a method to determine the route of a sailing vessel with the aid of deterministic algorithms. The method assumes that the area in which the route is to be determined is limited and the basic input data comprise the wind vector and the speed characteristic of the vessel. Compared to previous works of the authors, the present article additionally takes into account the effect of sea waves with the resultant resistance...
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Multi-objective Tabu-based Differential Evolution for Teleportation of Smart Virtual Machines in Private Computing Clouds
PublikacjaWe propose a multi-objective approach for using differential evolution algorithm with tabu search algorithm as an additional mutation for live migration (teleportation) of virtual machines. This issue is crucial in private computing clouds. Teleportation of virtual machines is supposed to be planned to determine Pareto-optimal solutions for several criteria such as workload of the bottleneck host, communication capacity of the...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Convex set of quantum states with positive partial transpose analysed by hit and run algorithm
PublikacjaThe convex set of quantum states of a composite K×K system with positive partial transpose is analysed. A version of the hit and run algorithm is used to generate a sequence of random points covering this set uniformly and an estimation for the convergence speed of the algorithm is derived. For K >3 or K=3 this algorithm works faster than sampling over the entire set of states and verifying whether the partial transpose is positive....
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublikacjaIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...
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A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor
PublikacjaThis paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure....
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Adrian Bekasiewicz dr hab. inż.
OsobyAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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The Way One Defines Specification Matters: On the Performance Criteria for Efficient Antenna Optimization in Aggregated Bi-Objective Setups
PublikacjaDesign of antenna structures for real-world applications is a challenging task that often involves addressing multiple design requirements at a time. Popular solution approaches to this class of problems include utilization of composite objectives. Although configuration of such functions has a significant effect on the cost and performance of the optimization, their specific structure is normally determined based on engineering...
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Efficient Multi-Fidelity Design Optimization of Microwave Filters Using Adjoint Sensitivity
PublikacjaA simple and robust algorithm for computationally efficient design optimiza-tion of microwave filters is presented. Our approach exploits a trust-region (TR)-based algorithm that utilizes linear approximation of the filter response obtained using adjoint sensitivity. The algorithm is sequentially executed on a family of electromagnetic (EM)-simulated models of different fidelities, starting from a coarse-discretization one, and...
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Improved-Efficacy EM-Based Antenna Miniaturization by Multi-Fidelity Simulations and Objective Function Adaptation
PublikacjaThe growing demands for integration of surface mount design (SMD) antennas into miniatur-ized electronic devices have been continuously imposing limitations on the structure dimen-sions. Examples include embedded antennas in applications such as on-board devices, picosatel-lites, 5G communications, or implantable and wearable devices. The demands for size reduction while ensuring a satisfactory level of the electrical and field...
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Rapid multi-objective design of integrated on-chip inductors by means of Pareto front exploration and design extrapolation
PublikacjaIdentification of the best trade-offs between conflicting design objectives allows for making educated design decisions as well as assessing suitability of a given component or circuit for a specific application. In case of inductors, the typical objectives include maximization of the quality factor and minimization of the layout area, as well as maintaining a required inductance at a given operating frequency. This work demonstrates...
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Space Mission Risk, Sustainability and Supply Chain: Review, Multi-Objective Optimization Model and Practical Approach
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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Comparison of Single and Multi-Population Evolutionary Algorithm for Path Planning in Navigation Situation
PublikacjaIn this paper a comparison of single and multi-population evolutionary algorithm is presented. Tested algorithms are used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of single-population and multi-population evolutionary algorithm is described....
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Framework of an Evolutionary Multi-Objective Optimisation Method for Planning a Safe Trajectory for a Marine Autonomous Surface Ship
PublikacjaThis paper represents the first stage of research into a multi-objective method of planning safe trajectories for marine autonomous surface ships (MASSs) involved in encounter situations. Our method applies an evolutionary multi-objective optimisation (EMO) approach to pursue three objectives: minimisation of the risk of collision, minimisation of fuel consumption due to collision avoidance manoeuvres, and minimisation of the extra...
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Numerically efficient algorithm for compact microwave device optimization with flexible sensitivity updating scheme
PublikacjaAn efficient trust-region algorithm with flexible sensitivity updating management scheme for electromagnetic (EM)-driven design optimization of compact microwave components is proposed. During the optimization process, updating of selected columns of the circuit response Jacobian is performed using a rank-one Broyden formula (BF) replacing finite differentiation (FD). The FD update is omitted for directions sufficiently well aligned...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Co-gasification of waste biomass-low grade coal mix using downdraft gasifier coupled with dual-fuel engine system: Multi-objective optimization with hybrid approach using RSM and Grey Wolf Optimizer
PublikacjaThe looming global crisis over increasing greenhouse gases and rapid depletion of fossil fuels are the motivation factors for researchers to search for alternative fuels. There is a need for more sustainable and less polluting fuels for internal combustion engines. Biomass offers significant potential as a feed material for gasification to produce gaseous fuel. It is carbon neutral, versatile, and abundant on earth. The present...
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Improving evolutionary multi-objective optimisation by niching
PublikacjaW pracy rozważa się ogólny problem optymalizacji ewolucyjnej i przestrzeniach wielowymiarowych, ze szczególnym uwzględnieniem mechanizmu niszowania, biorącego pod uwagę oceniane charakterystyki (funkcje przystosowania) osobników w generowanych nowych pokoleniach. Mechanizm ten służy do zapobiegania przedwczesnej zbieżności procedur ewolucyjnych poszukiwań oraz zwiększenia efektywności poszukiwań rozwiązań optymalnych. Polega on...
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublikacjaElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Multi-Objective Genetic Algorithm (MOGA) As a Feature Selecting Strategy in the Development of Ionic Liquids’ Quantitative Toxicity–Toxicity Relationship Models
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Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
PublikacjaIn order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublikacjaAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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Development of visual evoked potentials detection algorithm for objective perimetry
PublikacjaOpisano nową propozycję algorytmu detekcji potencjałów wzrokowych w zapisie EEG. Nowy algorytm bazuje na dekompozycji statystycznej ICA. Algorytm wstępnie przetestowano na danych eksperymentalnych.
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Reliable Multi-Stage Optimization of Antennas for Multiple Performance Figures in Highly-Dimensional Parameter Spaces
PublikacjaDesign of modern antenna structures needs to account for multiple performance figures and geometrical constraints. Fulfillment of these calls for the development of complex topologies described by a large number of parameters. EM-driven tuning of such designs is mandatory yet immensely challenging. In this letter, a new framework for multi-stage design optimization of multi-dimensional antennas with respect to several performance...
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A Bi-Objective Portfolio Optimization with Conditional Value-at-Risk
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Low-Cost Design Optimization of Microwave Passives Using Multi-Fidelity EM Simulations and Selective Broyden Updates
PublikacjaGeometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect operation and performance of these...
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Expedited Feature-Based Quasi-Global Optimization of Multi-Band Antenna Input Characteristics with Jacobian Variability Tracking
PublikacjaDesign of modern antennas relies—for reliability reasons—on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly...
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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
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Multi-Objective Traveling Salesman and Transportation Problems with Environmental Aspects
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A Reference Point Approach to Bi-Objective Dynamic Portfolio Optimization
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Objective relaxation algorithm for reliable simulation-driven size reduction of antenna structure
PublikacjaThis letter investigates reliable size reduction of antennas through electromagnetic-driven optimization. It is demonstrated that conventional formulation of the design task by direct footprint miniaturization with imposing constraints on electrical performance parameters may not lead to optimum results. The reason is that—in a typical antenna structure—only a few geometry parameters explicitly determine the antenna footprint,...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Pareto Task Assignments by an Adaptive Quantum-based Evolutionary Algorithm AQMEA
PublikacjaW pracy scharakteryzowano state_of_the_art w zakresie kwantowych algorytmów ewolucyjnych. Scharakteryzowano zasady efektywnego projektowania tej klasy algorytmów genetycznych. Podano wyniki uzyskane za pomocą kwantowego algorytmu ewolucyjnego AQMEA w zakresie wyznaczanie przydziałów zadań optymalnych w sensie Pareto.
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublikacjaDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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Multi gender genetic optimization of diagnostic observers.
PublikacjaW pracy przedstawiana jest nowa metoda rozwiązywania zadań wielokryterialnej optymalizacji. W omawianej metodzie wykorzystywana jest informacja o genetycznym rodzajniku osobnika w celu odpowiedniego rozróżnienia i agregacji wielu kryteriów. Charakterystyczne cechy mechanizmu są prezentowane na przykładzie wielokryterialnej optymalizacji detekcyjnych obserwatorów stanu.