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Optimal Lossy Matching by Pareto Fronts
IEEE Transactions on Circuits and Systems II: Express Briefs, 2008Although lossy matching is not a standard antenna matching technique, well-designed losses can facilitate wide-band matching of otherwise unmatchable antennas. The lossy matching designs developed in this paper are based on the Pareto front. These Pareto front computations permit the circuit designer to graphically select optimal gain-reflection ...
Jeffery C. Allen +2 more
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Pareto Fronts in Clinical Practice for Pinnacle
International Journal of Radiation Oncology*Biology*Physics, 2013Our aim was to develop a framework to objectively perform treatment planning studies using Pareto fronts. The Pareto front represents all optimal possible tradeoffs among several conflicting criteria and is an ideal tool with which to study the possibilities of a given treatment technique.
Tomas, Janssen +4 more
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2019
We consider multiobjective optimization problems affected by uncertainty, where the objective functions or the restrictions involve random variables. We are interested in the evaluation of statistics such as medians, quantiles and confidence intervals for the Pareto front.
Mohamed Bassi +3 more
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We consider multiobjective optimization problems affected by uncertainty, where the objective functions or the restrictions involve random variables. We are interested in the evaluation of statistics such as medians, quantiles and confidence intervals for the Pareto front.
Mohamed Bassi +3 more
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Ordinal classification using Pareto fronts
Expert Systems with Applications, 2015We present an ordinal classification method using Pareto fronts.We define Pareto fronts describing class boundaries for a separable sample.We propose to predict the object class using the nearest Pareto front boundary.The proposed method is illustrated by a problem of IUCN Red List categorization.
M. M. Stenina +2 more
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Regular Pareto Front Shape is not Realistic
2019 IEEE Congress on Evolutionary Computation (CEC), 2019Performance of evolutionary multi-objective and many-objective optimization algorithms is usually evaluated by computational experiments on a number of test problems. Thus, performance comparison results depend on the choice of test problems. For fair comparison, it is needed to use a wide variety of test problems with various characteristics. However,
Hisao Ishibuchi +2 more
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A Pareto Front Approach for Feature Selection
Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods, 2016This article deals with the multi-objective aspect of an hybrid algorithm that we propose to solve the feature subset selection problem. The hybrid aspect is due to the sequence of a filter and a wrapper method. The filter method reduces the exploration space by keeping subsets having good internal properties and the wrapper method chooses among the ...
Enguerran Grandchamp +2 more
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Computing the Entire Pareto Front
2021In the following three chapters we will address archivers that aim for Pareto front approximations of a given MOP. In the first step, we are interested in maintaining all non-dominated solutions that were computed during the run of an algorithm. That is, if we are given a set of candidate solutions .
Oliver Schütze, Carlos Hernández
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Multiclass Gene Selection Using Pareto-Fronts
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013Filter methods are often used for selection of genes in multiclass sample classification by using microarray data. Such techniques usually tend to bias toward a few classes that are easily distinguishable from other classes due to imbalances of strong features and sample sizes of different classes.
Jagath C. Rajapakse +1 more
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Layout-aware Pareto fronts of electronic circuits
2011 20th European Conference on Circuit Theory and Design (ECCTD), 2011Peer ...
Antonio Toro-Frías +3 more
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Computing Pareto fronts using distributed agents
Computers & Chemical Engineering, 2003Abstract Many problems that face a business decision maker are most accurately formulated as multi-objective optimization problems. However, actually solving these problems is a difficult and computationally expensive process. In this paper, we develop and use an agent-based optimization system for efficiently generating the non-dominated solution ...
John D. Siirola +2 more
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