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Optimization of accelerated life test design process for gears and bearings using equivalent damage method. [PDF]

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Kim JH, Kim BS, Park JH, Moon DJ, Kim S, Park YJ.   +5 more
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Pareto front feature selection

Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009
In this paper we use genetic programming (GP) for feature selection in binary classification tasks. Mathematical expressions built by GP transform the feature space in a way that the relevance of subsets of features can be measured using a simple relevance function.
Kourosh Neshatian, Mengjie Zhang
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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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Computing Gap Free Pareto Fronts

2021
So far, we have discussed the archiver that stores all non-dominated solutions out of the set of candidate solutions, and two archivers that are entirely based on the concept of \(\epsilon \)-dominance. While the applicability of \(ArchiveUpdateP_Q\) is restricted since it stores too many points during the run of the search process, the opposite can ...
Oliver Schütze, Carlos Hernández
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Computing Pareto fronts using distributed agents

Computers & Chemical Engineering, 2003
Abstract 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, Steinar Hauan, Arthur W. Westerberg   +2 more
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Multiclass Gene Selection Using Pareto-Fronts

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013
Filter 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, Piyushkumar A, Mundra   +1 more
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Computing the Entire Pareto Front

2021
In 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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Computing $$\epsilon $$-(approximate) Pareto Fronts

2021
As we have seen in the last chapter, if all non-dominated solutions that have been found during the search are added to the archiver, we can expect the resulting sequences of archives to go beyond any given threshold—if the search process is just executed long enough.
Oliver Schütze, Carlos Hernández
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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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