Search results for: OPTIMIZATION ALGORITHM
-
Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching
PublicationPurpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal...
-
EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm
PublicationIn the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking bisection algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using...
-
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...
-
Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublicationDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
-
Expedited Optimization of Passive Microwave Devices Using Gradient Search and Principal Directions
PublicationOver the recent years, utilization of numerical optimization techniques has become ubiquitous in the design of high-frequency systems, including microwave passive components. The primary reason is that the circuits become increasingly complex to meet ever growing performance demands concerning their electrical performance, additional functionalities, as well as miniaturization. Nonetheless, as reliable evaluation of microwave device...
-
Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublicationA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
-
Selection of energy storage units by genetic algorithm for mitigating voltage deviations
PublicationIn recent years, energy storage units have become very popular. They are applied both for economic and technical purposes. Unfortunately, the cost of such devices is still high and selecting their proper location and rated power have to be performed precisely. In this paper, a Genetic-Algorithm-based optimization method for selecting the best configuration of energy storage units in the power network is proposed. The presented...
-
Spectral measurement of birefringence using particle swarm optimization analysis
PublicationThe measurement of birefringence is useful for the examination of both technical and biological objects. One of the main problems is that the polarization state of light in birefringent media changes periodically. Without the knowledge of the period number, the birefringence of a given medium cannot be determined reliably. We propose to analyse the spectrum of light in order to determine the birefringence. We use a Particle Swarm...
-
EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublicationFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
-
Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublicationSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
-
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...
-
Fast EM-driven optimization using variable-fidelity EM models and adjoint sensitivities
PublicationA robust and computationally efficient technique for microwave design optimization is presented. Our approach exploits variable-fidelity electromagnetic (EM) simulation models and adjoint sensitivities. The low-fidelity EM model correction is realized by means of space mapping (SM). In the optimization process, the SM parameters are optimized together with the design itself, which allows us to keep the number...
-
Decisional DNA and Optimization Problem
PublicationMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
-
Generalized Pareto ranking bisection for computationally feasible multi-objective antenna optimization
PublicationMulti-objective optimization (MO) allows for obtaining comprehensive information about possible design trade-offs of a given antenna structure. Yet, executing MO using the most popular class of techniques, population-based metaheuristics, may be computationally prohibitive when full-wave EM analysis is utilized for antenna evaluation. In this work, a low-cost and fully deterministic MO methodology is introduced. The proposed generalized...
-
SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION
PublicationThe paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...
-
Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublicationIn this paper, a novel meta-heuristic method for evaluation of digital filter stability is presented. The proposed method is very general because it allows one to evaluate stability of systems whose characteristic equations are not based on polynomials. The method combines an efficient evolutionary algorithm represented by the particle swarm optimization and the phase analysis of a complex function in the characteristic equation....
-
Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn 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...
-
Controlling nodal displacement of pantographic structures using matrix condensation and interior-point optimization: A numerical and experimental study
PublicationThis study presents an innovative approach for the precise control of nodal displacements in pantographic structures. The method is founded on the Matrix Condensation of Force Method, seamlessly integrated with an Interior Point Optimization algorithm. This combination offers a unique advantage by allowing users to manipulate displaced nodes within a defined coordination domain. Furthermore, this approach introduces the Interior...
-
Complex multidisciplinary optimization of turbine blading systems
PublicationThe paper describes the methods and results of direct optimization of turbine blading systems using a software package Opti_turb. The final shape of the blading is obtained from minimizing the objective function, which is the total energy loss of the stage, including the leaving energy. The current values of the objective function are found from 3D RANS computations (from a code FlowER) of geometries changed during the process...
-
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...
-
Patch size setup and performance/cost trade-offs in multi-objective antenna optimization using domain patching technique
PublicationA numerical study concerning multi-objective optimization of antenna structures using sequential domain patching (SDP) technique has been presented. We investigate the effect of various setups of the patch size on the operation of the SDP algorithm and possible trade-offs concerning the quality of the Pareto set found by SDP and the computational cost of the optimization process. Our considerations are illustrated using a UWB monopole...
-
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...
-
Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor
PublicationWastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied...
-
Using River Formation Dynamics Algorithm in Mobile Robot Navigation
PublicationRiver Formation Dynamics is a heuristic optimization algorithm based on the manner, in which drops of water form the river bed. The idea is to imitate the movement of drops on the edges between given nodes thus performing a search based on their height, which is modified through the mechanism of soil erosion and sediment deposition. In this way decreasing gradients are constructed, and these are followed by subsequent drops to...
-
Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublicationIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
-
Selection of optimal location and rated power of capacitor banks in distribution network using genetic algorithm
PublicationIn this paper, the problem of placement and rated power of capacitor banks in the Distribution Network (DN) is considered. We try to suggest the best places for installing capacitor banks and define their reactive power. The considered formulation requires the optimization of the cost of two different objectives. Therefore the use of properly multiobjective heuristic optimization methods is desirable. To solve this problem we use...
-
Simulation model for evaluation of QoS routing algorithm in large packet networks
PublicationThe variety of traffic transferred via current telecommunication networks includes also voice, which should meet quality requirements. One of mechanisms, which can support QoS in current packet networks, is routing. There exist many routing proposals which should introduce the QoS into the network but practically they don't. Following paper presents the realization of simulation model for evaluation of a new routing algorithm DUMBRA...
-
Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublicationIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
-
Multicriteria Evolutionary Weather Routing Algorithm in Practice
PublicationThe Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid-propulsion or motor-driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization...
-
Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
-
Computer-aided reconstruction of the railway track axis geometrical shape
PublicationIn the paper a method of the railway track axis geometrical shape identification in a horizontal plane, directly from the continuous satellite measurements, is presented. In this method, an algorithm for the design of railway track sections located in the horizontal arc is used. The algorithm uses an analytical description of the layout by means of suitable mathematical formulas. The design procedure has a universal character and...
-
Computational Bar Size Optimization of Single Layer Dome Structures Considering Axial Stress and Shape Disturbance
PublicationA computational method is proposed in this paper to minimize the material usage in the construction of modern spatial frame structures by prestressing a minimal number of members. The computational optimization is conducted in two steps. Firstly, a numerical model of a single-layer dome structure is used to minimize the cross-sectional area through several iterations. Different assumed ratios (r) ranging from 0.95 to 0.75 are multiplied...
-
Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
-
On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
-
Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublicationIn the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational...
-
Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
-
Shared processor scheduling
PublicationWe study the shared processor scheduling problem with a single shared processor to maximize total weighted overlap, where an overlap for a job is the amount of time it is processed on its private and shared processor in parallel. A polynomial-time optimization algorithm has been given for the problem with equal weights in the literature. This paper extends that result by showing an (log)-time optimization algorithm for a class...
-
Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
-
On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublicationThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
-
Rapid design closure of microwave components by means of feature-based optimization and adjoint sensitivities
PublicationIn this article, fast design closure of microwave components using feature-based optimization (FBO) and adjoint sensitivities is discussed. FBO is one of the most recent optimization techniques that exploits a particular structure of the system response to “flatten” the functional landscape handled during the optimization process, which leads to reducing its computational complexity. When combined with gradient-based search involving...
-
Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine 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...
-
Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublicationElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
-
Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
-
RANS-based design optimization of dual-rotor wind turbines
PublicationPurpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine...
-
Development of Local IDF-formula Using Controlled Random Search Method for Global Optimization
PublicationThe aim of the study is to present the effective and relatively simple empirical approach to rainfall Intensity-Duration-Frequency-formulas development, based on Controlled Random Search (CRS) for global optimization. The approach is mainly dedicated to the cases in which the commonly used IDF-relationships do not provide satisfactory fit between simulations and observations, and more complex formulas with higher number of parameters...
-
Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublicationA computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based...
-
Ship weather routing optimization with dynamic constraints based on reliable synchronous roll prediction
PublicationShip routing process taking into account weather conditions is a constrained multi-objective optimization problem and it should consider various optimization criteria and constraints. Formulation of a stability-related, dynamic route optimization constraint is presented in this paper. One of the key objectives of a cross ocean sailing is finding a compromise between ship safety and economics of operation. This compromise should...
-
High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublicationDesign of modern antenna systems has become highly dependent on computational tools, especially full-wave electromagnetic (EM) simulation models. EM analysis is capable of yielding accurate representation of antenna characteristics at the expense of considerable evaluation time. Consequently, execution of simulation-driven design procedures (optimization, statistical analysis, multi-criterial design) is severely hindered by the...
-
Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas
PublicationA surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through...
-
Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...