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The relationship between multi-objective robustness concepts and set-valued optimization
2014
Fixed Point Theory and Applications
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In this paper, we discuss the connection between concepts of robustness for multi-objective optimization problems and set order relations. ...
Furthermore, we derive new concepts of robustness for multi-objective optimization problems. ...
In [, ] robust solutions of multi-objective optimization problems are introduced in the following way. ...
doi:10.1186/1687-1812-2014-83
fatcat:nci5rndw2jfirhjnasg6poasge
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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Multi-objective combinatorial optimization (MOCO) problems, apart from being notoriously difficult and complex to solve in reasonable computational time, they also exhibit high levels of instability in ...
In this work we propose an integrated methodology to measure and analyze the robustness of MOCO problems, and more specifically multi-objective integer programming ones, given the imperfect knowledge of ...
A concept of robustness in MOO was also introduced by Figueira et al. [10] , especially in the case of interactive multi-objective optimization. ...
doi:10.1016/j.omega.2014.11.005
fatcat:bo22xeglovhnzk7vrwkljfjazi
On the properties of lexicographic tolerable robust solution sets for uncertain multi-objective optimization problems
2021
Carpathian Journal of Mathematics
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This study provides the important properties of the lexicographic tolerable robust solution for uncertain multi-objective optimization problems which was introduced by Boriwan et al. ...
Minmax robustness for multi-objective optimization problems. European Journal of Operational Research. 239 (2014), no. 1, 17-31.], are provided. ...
These two issues have been studied in the areas of multi-objective optimization and robust optimization, respectively. ...
doi:10.37193/cjm.2022.01.06
fatcat:3p6tg3z2efb53b3l37rx7exe2m
On the properties of lexicographic tolerable robust solution sets for uncertain multi-objective optimization problems
2021
Carpathian Journal of Mathematics
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This study provides the important properties of the lexicographic tolerable robust solution for uncertain multi-objective optimization problems which was introduced by Boriwan et al. ...
Minmax robustness for multi-objective optimization problems. Eur. J. Oper. Res. 239 (2014), no. 1, 17–31.], are provided. ...
These two issues have been studied in the areas of multi-objective optimization and robust optimization, respectively. ...
doi:10.37193/cjm.2021.03.05
fatcat:fp27iewx3nd4bpfx355bjhltlu
Robust optimization of SoC architectures: A multi-scenario approach
2008
2008 IEEE/ACM/IFIP Workshop on Embedded Systems for Real-Time Multimedia
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The resulting robust solution is characterized by a multi-objective optimality over the set of considered scenarios. ...
The problem of the robust optimization has been treated as a minimization of a geometric mean of the objective functions computed over each uncertainty scenario and it is solved with a multi-criteria decision ...
We introduce as well some robust optimization techniques. ...
doi:10.1109/estmed.2008.4696986
dblp:conf/estimedia/PalermoSZ08
fatcat:ejk5mob7ibfb7k6wq4v4lqxq3e
Determining a Robust, Pareto Optimal Geometry for a Welded Joint
2014
Advanced Materials Research
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In this paper a methodology has been proposed that allows a robust design to be selected from the Pareto optimal set. This methodology has been used to determine a robust geometry for a welded joint. ...
Multi-criteria optimization problems are known to give rise to a set of Pareto optimal solutions where one solution cannot be regarded as being superior to another. ...
It has been recognized that many engineering design problems have multiple objectives and approaches for multi criteria optimization in design were introduced by [2] for example. ...
doi:10.4028/www.scientific.net/amr.1016.39
fatcat:v3rfkcja2vfzpo6dxaaao2ipee
Robust carving for non-Lambertian objects
2004
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
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The former considers a general specularity that may introduce both reflectance models and robust statistics, while the latter is based on pixel homogeneity and continuity in individual images. ...
We introduce a robust multiview photo-consistency function and a single-view visualconsistency function. ...
Global optimization We choose the general graph-cut optimization introduced in [20] . ...
doi:10.1109/icpr.2004.1334483
dblp:conf/icpr/ZengPQ04
fatcat:aar775zmtffxlh5ojtx2sucxsy
Introducing a watermarking with a multi-objective genetic algorithm
2005
Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05
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The problem is stated as a multi-objective optimization problem (MOP), that involves the simultaneous minimization of distortion and robustness criteria. ...
The algorithm searches for the optimal localization of the DCT of an image to place the mark image DCT coefficients. ...
Combined optimization of the distortion and the robustness can be stated as a multi-objective optimization. ...
doi:10.1145/1068009.1068383
dblp:conf/gecco/DiazR05
fatcat:lnbwg3gz7zbcbg2wgrzpvgk2dq
Robust Multi-Objective Optimization of Chromatographic Rare Earth Element Separation
2017
Advances in Chemical Engineering and Science
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In this study, a model-based robust multi-objective optimization was carried out for batch-wise chromatographic separation of the rare earth elements samarium, europium and gadolinium, which was considered ...
was introduced. ...
The current work complements the previous studies by introducing robust multi-objective optimization. ...
doi:10.4236/aces.2017.74034
fatcat:yw246gpawfbqph3tyzq6cq3opm
Intelligent Watermarking with Multi-objective Population Based Incremental Learning
2010
2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
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In this paper, we propose a multi-objective Population Based Incremental Learning module for an intelligent watermarking system for grayscale images to optimize embedding watermarks that satisfy the trade-off ...
The multi-objective formulation provides set of non-dominated solutions rather than single solution, which allows tuning the quality and robustness for several attacks, without the need for an expensive ...
The Multi-objective PBIL optimizer used is detailed in Algorithm 1. ...
doi:10.1109/iihmsp.2010.40
dblp:conf/iih-msp/RabilSG10
fatcat:26mbbrszyjcm3bezylqhotvgzq
Robust optimization of multi-scenario many-objective problems with auto-tuned utility function
2020
figshare.com
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The main focus in optimization studies, including multi-objective and multi-scenario optimization, is placed on finding the global optimum or global Pareto-optimal solutions, representing the best possible ...
The method can be used universally where the robust optimum is required for a model having multi-scenario and multi-objective properties. ...
Two-objective Multi-scenario Multi-variable Test Function This test function is a two-objective optimization problem with three design variables, which has already been used for testing robust optimization ...
doi:10.6084/m9.figshare.12848954.v1
fatcat:pxz4vf2yofea3n3kuvs55p6dm4
The Lexicographic Tolerable Robustness Concept for Uncertain Multi-Objective Optimization Problems: A Study on Water Resources Management
2020
Sustainability
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In this study, we introduce a robust solution concept for uncertain multi-objective optimization problems called the lexicographic tolerable robust solution. ...
This approach is advantageous for the practical implementation of problems in which the solution should satisfy priority levels in the objective function and the worst performance vector of the solution ...
Methodology In this section, we introduce the concept of lexicographic tolerable robust solution for an uncertain multi-objective optimization problem. ...
doi:10.3390/su12187582
fatcat:tevsqjuwwncr3ifmn3vbnj3w6y
Robust Optimal Experiment Design: A Multi-Objective Approach
2012
IFAC Proceedings Volumes
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This weighted sum has well known drawbacks in a Multi-Objective Optimisation approach. ...
In recent work a formulation using an implicit weighted sum approach is proposed where the objective function is split in a nominal optimal experiment design part and a robust counterpart. ...
ACKNOWLEDGEMENTS Work supported in parts by Projects PFV/10/002, OPTEC (Centreof-Excellence Optimisation in Engineering) and KP/09/005 SCORES-4CHEM knowledge platform of the Katholieke Universiteit Leuven ...
doi:10.3182/20120215-3-at-3016.00122
fatcat:u7zvu6nwujasjepn5f2lsgphm4
Developing a Multi-objective Multi-Disciplinary Robust Design Optimization Framework
2021
Scientia Iranica. International Journal of Science and Technology
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This study aims to provide an e cient Multi-Objective Multidisciplinary Robust Design Optimization (MOMRDO) framework. ...
The results showed that this method is a fast and e ective method for the multi-objective optimization design of complex systems, and it can also be used in other engineering applications. ...
Optimization (MOMDO) and Multi-Objective Robust Multi-disciplinary Design Optimization (MORMDO) results are presented in this section. ...
doi:10.24200/sci.2021.55306.4159
fatcat:zlcb4eco4bfplat6sj7fiuxybq
Evolutionary Multi-Objective Robust Optimization
[chapter]
2008
Advances in Evolutionary Algorithms
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In multi-objective robust optimization the aim is to obtain a set of Pareto solutions that are, at the same time, multi-objectively robust and Pareto optimal. ...
Evolutionary Multi-Objective Robust Optimization ...
doi:10.5772/6127
fatcat:qn4pytwen5adhpxwqxogzvpp3m
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