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Wyniki wyszukiwania dla: PARETO-OPTIMALITY
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Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Hierarchiczna Pareto-optymalizacja obserwatorów detekcyjnych
PublikacjaW niniejszym rozdziale omawiana jest nowa metoda nieostrego, eksperckiego uporządkowania funkcji kryterialnych odpowiednich dla ewolucyjnych i chmarowych podejść do (iteracyjnego) rozwiązywania wielokryterialnych zadań optymalizacyjnych, w których korzysta się z idei rodzajnika genetycznego opartego na podziale zbioru funkcji celu na odpowiednie podzbiory (subkryteria). Podział ten odnosi się do pokrewieństwa w przestrzeni kryterialnej...
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Pareto-optymalne szeregowanie zadań wieloprocesorowych na procesorach dedykowanych
PublikacjaProblem szeregowania jednostkowych zadań wieloprocesorowych na maszynach dedykowanych można modelować przy pomocy hipergrafów. Znamy kilka klas hipergrafów, dla których szeregowanie z kryterium kosztu całkowitego jest wielomianowe. Pokażemy jak przy pomocy modelu z kosztem całkowitym można rozwiązać problemy z innymi kryteriami znanymi z teorii szeregowania, oraz jak rozwiązać problemy dwukryterialne.
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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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Generalized Pareto ranking bisection for computationally feasible multi-objective antenna optimization
PublikacjaMulti-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...
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublikacjaThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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Pareto Optimal Decisions in Multi-Criteria Decision Making Explained with Construction Cost Cases
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Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublikacjaA 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...
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Rapid multi-objective design optimization of miniaturized impedance transformer by Pareto front exploration
PublikacjaFast multi-objective optimization of compact impedance transformer is discussed. A set of alternative designs representing possible trade-offs between conflicting design criteria, i.e., electrical performance (here, wideband matching) and the structure size, is obtained through Pareto front exploration by means of surrogate-assisted methods.
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EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm
PublikacjaIn 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...
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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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Minimizing Greenhouse Gas Emissions From Ships Using a Pareto Multi-Objective Optimization Approach
PublikacjaTo confront climate change, decarbonization strategies must change the global economy. According to statements made as part of the European Green Deal, maritime transport should also become drastically less polluting. As a result, the price of transport must reflect the impact it has on the environment and on health. In such a framework, the purpose of this paper is to suggest a novel method for minimizing emissions...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
PublikacjaDesign of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with topology evolution, are followed by a meticulous adjustment of the structure dimensions. The latter is necessary to boost the antenna performance as much as possible, and often requires handling several and often conflicting objectives, pertinent to both electrical and field properties...
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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublikacjaDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublikacjaThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublikacjaIn 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...
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Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors
PublikacjaThis work presents a novel approach to computationally efficient Pareto front identification for variable-turn on-chip inductors. The final outcome is a set of solutions that correspond to the best trade-offs between conflicting design objectives. Here, we consider minimising inductor area and, simultaneously, maximising its quality factor, while maintaining a specified inductance value at a given operating frequency. As opposed...
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Multi-fidelity aerodynamic design trade-off exploration using point-by-point Pareto set identification
PublikacjaAerodynamic design is inherently a multi-objective optimization (MOO) problem. Determining the best possible trade-offs between conflicting aerodynamic objectives can be computationally challenging when carried out directly at the level of high-fidelity computational fluid dynamics simulations. This paper presents a computationally cheap methodology for exploration of aerodynamic design trade-offs. In particular, point-by-point...
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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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Parity vertex colouring of graphs
PublikacjaA parity path in a vertex colouring of a graph is a path along which each colour is used an even number of times. Let Xp(G) be the least number of colours in a proper vertex colouring of G having no parity path. It is proved that for any graph G we have the following tight bounds X(G) <= Xp(G) <=|V(G)|− a(G)+1, where X(G) and a(G) are the chromatic number and the independence number of G, respectively. The bounds are improved for...