Results 251 to 260 of about 14,697 (286)

Pareto Front Estimation for Decision Making

Evolutionary Computation, 2014
The set of available multi-objective optimisation algorithms continues to grow. This fact can be partially attributed to their widespread use and applicability. However, this increase also suggests several issues remain to be addressed satisfactorily. One such issue is the diversity and the number of solutions available to the decision maker (DM). Even
Ioannis Giagkiozis, Peter J. Fleming
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Ordinal classification using Pareto fronts

Expert Systems with Applications, 2015
We 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, Mikhail P. Kuznetsov, Vadim V. Strijov   +2 more
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On Analysis of Irregular Pareto Front Shapes

2021
After decades of effort, evolutionary algorithms have been able to solve a variety of multiobjective optimisation problems with diverse characteristics. However, the presence of irregularity in the Pareto-optimal front is increasingly recognised as a big challenge to some well-established algorithms.
Shouyong Jiang, Jinglei Guo, Bashar Alhnaity, Qingyang Zhang 0002   +3 more
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Pareto Fronts in Clinical Practice for Pinnacle

International Journal of Radiation Oncology*Biology*Physics, 2013
Our 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, Zdenko, van Kesteren, Gijs, Franssen, Eugène, Damen, Corine, van Vliet   +4 more
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Statistics of Pareto Fronts

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, Emmanuel Pagnacco, Eduardo Souza de Cursi, Rachid Ellaia   +3 more
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Approximative Pareto Front Identification

2015 IEEE Symposium Series on Computational Intelligence, 2015
Techniques from multi-objective optimization are incorporated into the stochastic multi-armed bandit (MAB) problem to improve performance when the rewards obtained from pulling an arm are random vectors instead of random variables. We call this problem the stochastic multi-objective MAB (or MOMAB) problem.
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Optimal Lossy Matching by Pareto Fronts

IEEE Transactions on Circuits and Systems II: Express Briefs, 2008
Although 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, Diana Arceo, Peder Hansen   +2 more
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Regular Pareto Front Shape is not Realistic

2019 IEEE Congress on Evolutionary Computation (CEC), 2019
Performance 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, Linjun He, Ke Shang 0004   +2 more
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Calculating Complete and Exact Pareto Front for Multiobjective Optimization: A New Deterministic Approach for Discrete Problems

IEEE Transactions on Cybernetics, 2013
Searching the Pareto front for multiobjective optimization problems usually involves the use of a population-based search algorithm or of a deterministic method with a set of different single aggregate objective functions.
Xiao-Bing Hu, Ezequiel A Di Paolo
exaly   +2 more sources

A Pareto Front Approach for Feature Selection

Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods, 2016
This 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, Mohamed Abadi, Olivier Alata   +2 more
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