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Methods for multi-dimensional robustness optimization in complex embedded systems
2007
Proceedings of the 7th ACM & IEEE international conference on Embedded software - EMSOFT '07
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We demonstrate the robustness optimization methods by means of a small but realistic case study. ...
Since determining multi-dimensional robustness is computationally expensive we introduce efficient exploration methods based on a stochastic sensitivity analysis technique capable of deriving upper and ...
Given a set of possible parameter configurations C for S and a set of weights W = {w 1 , . . . , w n } with ∀ i w i ≥ 1, the dynamic robustness gain which can be achieved through dynamic system reconfigurability ...
doi:10.1145/1289927.1289947
dblp:conf/emsoft/HamannRE07
fatcat:6k2pnekir5gxlijhxdu4tm7bey
Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection
2015
Omega : The International Journal of Management Science
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We propose measures to assess the robustness of each specific Pareto optimal solution (POS), as well as the robustness of the entire Pareto set (PS) as a whole. ...
their results in case of uncertainty, which often deviate far from optimality. ...
These methods result in the generation of the whole set of efficient solutions (Pareto set) that includes all the Pareto optimal solutions (POS). ...
doi:10.1016/j.omega.2014.11.005
fatcat:bo22xeglovhnzk7vrwkljfjazi
Competitive coevolutionary algorithm for robust multi-objective optimization: The worst case minimization
2016
2016 IEEE Congress on Evolutionary Computation (CEC)
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The decision maker must perform an extra step of sensitivity analysis in which each solution should be verified for its robustness, but this post optimization procedure makes the optimization process expensive ...
In order to avoid this situation, many researchers are developing Robust MOO, where uncertainties are incorporated in the optimization process, which seeks optimal robust solutions. ...
The third author wants to acknowledge the support of FEDER funds through the COMPETE 2020 Programme and National Funds through FCT -Portuguese Foundation for Science and Technology under the project UID ...
doi:10.1109/cec.2016.7743846
dblp:conf/cec/MeneghiniGG16
fatcat:uwrmfu6fojejzetcfeka4yzum4
Robust design and optimization of composite stiffened panels in post-buckling
2014
Structural And Multidisciplinary Optimization
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Multilevel optimization including progressive failure analysis and robust design optimization for composite stiffened panels, in which the ultimate load that a post-buckled panel can bear is maximized ...
the material characterization up to trade constraints, through preliminary analysis and detailed design. ...
This post buckling strength capacity has significant potential for weight saving. ...
doi:10.1007/s00158-014-1136-5
fatcat:5lv3oci2nzh3vjslz54u2spe54
Robust design of microbial strains
2012
Bioinformatics
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We are capable to combine the exploration of species, reactions, pathways and knockout parameter spaces with the Pareto optimality principle. ...
Our framework performs three tasks: it evaluates the parameter sensitivity of the microbial model, searches for the optimal genetic or fluxes design, and finally calculates the robustness of the microbial ...
In the post-processing step, suitable solutions (selected from the Pareto front) are subjected to Global, Local and Pathway-oriented Robustness Analysis. ...
doi:10.1093/bioinformatics/bts590
pmid:23044547
fatcat:skldltn7b5dtlo4wxuwwxuzg5y
Robust structural damage identification based on multi-objective optimization
2009
International Journal for Numerical Methods in Engineering
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Another merit of the proposed approach is quantified confidence in damage detection through processing Pareto-optimal solutions. ...
Its non-domination-based convergence provides a stronger constraint which enables robust identification of damages with lower false-negative detection rate. ...
Finally, a set of well-distributed Pareto optimal solutions are obtained. ...
doi:10.1002/nme.2726
fatcat:4igy37bdvbepxkniv2wissi4qm
A Computational Multi-Criteria Optimization Approach to Controller Design for Physical Human-Robot Interaction
[article]
2020
arXiv
pre-print
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In particular, we propose a Pareto optimization framework that allows the designer to make informed decisions by thoroughly studying the trade-off between stability robustness and transparency. ...
In this paper, we propose a multi-criteria optimization framework, which jointly optimizes the stability robustness and transparency of a closed-loop pHRI system for a given interaction controller. ...
The Scientific and Technological Research Council of Turkey (TUBITAK) supported this work under contract EEEAG-117E645. ...
arXiv:2006.11218v1
fatcat:xm6padbxwbafbaxjhd4jrsts6a
Multi-Metric Optimization Using Ensemble Tuning
2013
North American Chapter of the Association for Computational Linguistics
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We study the effectiveness of our methods through experiments on multiple as well as single reference(s) datasets. ...
Pareto-optimality is a natural way to think about multi-metric optimization (MMO) and our methods can effectively combine several Pareto-optimal solutions, obviating the need to choose one. ...
Similar to Duh et al. (2012) , we use five different BLEU:RIBES weight settings, viz. (0.0, 1.0), (0.3, 0.7), (0.5, 0.5), (0.7, 0.3) and (1.0, 0.0), marked L1 through L5 or P1 through P5. ...
dblp:conf/naacl/SankaranSD13
fatcat:lq4xkvwjrfeqlcqcsphub7hnia
Reduction environmental effects of civil aircraft through multi-objective flight plan optimisation
2010
IOP Conference Series: Materials Science and Engineering
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Numerical results show that the method is able to capture a set of useful trade-offs that reduce NOx and CO 2 (minimum mission fuel weight). ...
The objectives of first optimisation are to maximise range of aircraft while minimising NOx with constant mission fuel weight. ...
Post-Processing including plotting Pareto optimal front and their mission characteristics, and generating comparison report between the baseline and Pareto optimal solutions. ...
doi:10.1088/1757-899x/10/1/012197
fatcat:4cm3tr4dmjbodaimjfmsuyrzki
Reliability based multi-objective robust design optimization of steel moment resisting frame considering spatial variability of connection parameters
2014
Engineering structures
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Finally, the authors demonstrate the use of proposed robust design optimization approach to obtain a Pareto Front, a collection of optimal designs that are optimized for both reliability and cost. ...
To reduce computation demands in calculating the seismic response variation, design parameters that have a negligible effect on seismic response are first eliminated through sensitivity analysis. ...
In multi-objective optimization, the solution is usually a set of solutions known as a 'Pareto front' rather than a single unique solution. ...
doi:10.1016/j.engstruct.2014.07.024
fatcat:wjir7v77hbf4tfjecsgopl4gpa
Robust geotechnical design of braced excavations in clays
2014
Structural Safety
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(a signal of the design robustness) and the cost were optimized with the strict safety constraints. ...
The robust design of the braced excavation system (including soil, wall, and support) was then formulated as a multi-objective optimization problem, in which the variation of the maximum wall deflection ...
Acknowledgments The study on which this paper is based was supported in part by National Science Foundation through Grant CMMI-1200117 (''Transforming Robust Design Concept into a Novel Geotechnical Design ...
doi:10.1016/j.strusafe.2013.05.003
fatcat:rwyilryrvfdwniuactno2ngbga
Robust Design Optimization and Emerging Technologies for Electrical Machines: Challenges and Open Problems
2020
Applied Sciences
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The goal of this paper is to give an overview of the widely used optimization techniques in electrical machinery and to summarize the challenges and open problems in the applications of the robust design ...
optimization and the prospects in the case of the newly emerging technologies. ...
best solution, only a leader set of the Pareto-optimal solutions. ...
doi:10.3390/app10196653
doaj:9bb6606346f14e0ba83de62fe04591ff
fatcat:s7igiflkafbundtozrzklinnk4
Multi-objective design of post-tensioned concrete road bridges using artificial neural networks
2017
Structural And Multidisciplinary Optimization
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After this process, the Pareto set is actualized and improved through 87 5 exact analysis. ...
ANNs are trained through the results of previous bridge 11 performance evaluations. Then, ANNs are used to evaluate the constraints and provide a direction 12 towards the Pareto front. ...
Acknowledgments
443 The authors acknowledge the financial support of the Spanish Ministry of Economy and 444 Competitiveness, along with FEDER funding (BRIDLIFE Project: BIA2014-56574-R) and the ...
doi:10.1007/s00158-017-1653-0
fatcat:ba5a6rol4bhf3o3rrjmgfceol4
Multi-Objective Automatic Machine Learning with AutoxgboostMC
[article]
2021
arXiv
pre-print
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2019 pre-print arXiv:1908.10796v1 fatcat:3dpl2nemubeznbw25zc3kuhzim
They often combine techniques from many different sub-fields of machine learning in order to find a model or set of models that optimize a user-supplied criterion, such as predictive performance. ...
Current AutoML frameworks either do not allow to optimize such secondary criteria or only do so by limiting the system's choice of models and preprocessing steps. ...
over a set of measures. ...
arXiv:1908.10796v2
fatcat:5jtzi2jetrfstok2xtt36vmlly
Meta-model-based multi-objective optimization for robust color reproduction using hybrid diffraction gratings
2020
Optics Express
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We propose an efficient and versatile optimization scheme, based on the combination of multi-objective genetic algorithms and neural-networks, to reproduce specific colors through the optimization of the ...
The strength of our approach lies in the possibility to simultaneously optimize different contradictory objectives, avoiding time-consuming electromagnetic calculations. ...
Furthermore, through a post-optimization procedure we discuss robustness of the optimal solutions found and their sensitivity to fabrication errors. ...
doi:10.1364/oe.28.003388
pmid:32122008
fatcat:fpqz5f3wafg2fdxtcewn425xwy
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