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Personalized search for social media via dominating verbal context
2016
Neurocomputing
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Adaptive Operator Selection with Bandits for Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation, 18(1): 114-130, 2014. ...
A Novel Slicing Based Algorithm to Calculate Hypervolume for Multi-Objective Optimization Problems. ICIC Express Letters: An International Journal of Research and Surveys, 4(4): 1113-1120, 2010. ...
doi:10.1016/j.neucom.2014.12.109
fatcat:dpzdo6mtrrbatpiz2jdcglq3ki
Evolutionary Algorithms Based on Decomposition and Indicator Functions: State-of-the-art Survey
2016
International Journal of Advanced Computer Science and Applications
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based information, local search optimizers, multiple ensemble search operators together with self-adaptive strategies, metaheuristics, mating restriction approaches, statistical sampling techniques, integration ...
Multi-Objective Evolutionary Algorithms (MOEAs) play a dominant role in solving problems with multiple conflicting objective functions. ...
A novel smart multi-objective particle swarm optimization based decomposition (SDMOPSO) is recently suggested in [2] for solving ZDT test problems [198] . ...
doi:10.14569/ijacsa.2016.070274
fatcat:3oleqyfntzdz5hwkd3f5df56qi
Bio-Inspired Learning and Adaptation for Optimization and Control of Complex Systems
2019
Complexity
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Wang et al. addressed a maintenance plan optimization problem for building energy retrofitting with a novel multiscale differential evolution based algorithm. B. ...
decomposition for multiobjective optimization. ...
decomposition for multiobjective optimization. ...
doi:10.1155/2019/9325364
fatcat:lzyijulawfcabnm3zlw6sd2txa
Multiobjective evolutionary algorithms: A survey of the state of the art
2011
Swarm and Evolutionary Computation
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By evolving a population of solutions, multiobjective evolutionary algorithms (MOEAs) are able to approximate the Pareto optimal set in a single run. ...
It covers algorithmic frameworks such as decomposition-based MOEAs (MOEA/Ds), memetic MOEAs, coevolutionary MOEAs, selection and offspring reproduction operators, MOEAs with specific search methods, MOEAs ...
An MOEA based on decomposition: MOEA/D A multiobjective evolutionary algorithm based on decomposition (MOEA/D) [28] is a recent multiobjective evolutionary algorithmic framework. ...
doi:10.1016/j.swevo.2011.03.001
fatcat:jfcghitjp5ap5he4d3ackhhjsu
Guest Editorial Evolutionary Computation Meets Deep Learning
2021
IEEE Transactions on Evolutionary Computation
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for image classification, called evolving deep convolutional variational autoencoder (EvoVAE), based on a genetic algorithm (GA). ...
Evolutionary Algorithm for Deep Learning" by Zhang et al. proposes an adaptive scalable neural architecture search method (AS-NAS) based on the reinforced evolutionary algorithm (EA) and variable architecture ...
doi:10.1109/tevc.2021.3096336
fatcat:ajhq2kzvkbf7zkswroldxrufp4
Decomposition-Based Multiobjective Optimization for Constrained Evolutionary Optimization
2018
IEEE Transactions on Systems, Man & Cybernetics. Systems
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In this paper, we make use of decomposition-based multiobjective optimization to solve constrained optimization problems (COPs). ...
Moreover, for some extremely complicated COPs, a restart strategy is introduced to help the population jump out of a local optimum in the infeasible region. ...
Extensive and systematic experiments verified that the following. 1) The weight vector adjusting strategy is an effective way to adapt decomposition-based multiobjective optimization for COPs, by producing ...
doi:10.1109/tsmc.2018.2876335
fatcat:ckfi2mfvozfwbfswauflkeshym
A Survey of Multiobjective Evolutionary Algorithms Based on Decomposition: Variants, Challenges and Future Directions
2020
IEEE Access
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Decomposition methods and evolution mechanisms enable multiobjective evolutionary algorithms based on decomposition (MOEA/D) to tackle these complex optimization problems efficiently. ...
INDEX TERMS Multiobjective evolutionary algorithms based on decomposition (MOEA/D), decomposition method, weight vector generation method, evolutionary operator, many-objective optimization. ...
Based on their previous work, the R-MEAD (a reference point based multiobjective evolutionary algorithm with decomposition), Mohammadi et al. [46] developed a novel algorithm termed R-MEAD2. ...
doi:10.1109/access.2020.2973670
fatcat:brejxae75nbl7dvhg2grne4lni
Table of contents
2021
IEEE Transactions on Cybernetics
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Zhu 2712 Stochastic Dual Simplex Algorithm: A Novel Heuristic Optimization Algorithm . . . S. M. Zandavi, V. Y. Y. Chung, and A. ...
Liu2625 The Collaborative Local Search Based on Dynamic-Constrained Decomposition With Grids for Combinatorial Multiobjective Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/tcyb.2021.3071166
fatcat:2rhnoufzxbeh3k7xhwyenvwwvu
Special issue on multi-objective reinforcement learning
2017
Neurocomputing
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We also wish to thank the editors of Neurocomputing who supervised an independent review process for those papers for which we had a conflict of interest. ...
Acknowledgements We would like to thank all of the authors who submitted their work for this issue, as well as the reviewers who generously gave their time and expertise during the review process. ...
Another bi-objective environment that has been used to evaluate a novel multi-objective RL algorithm is the Linked Rings problem [3] . ...
doi:10.1016/j.neucom.2017.06.020
fatcat:bw6mnryx3fbitm7rnj6wehopsm
A review of population-based metaheuristics for large-scale black-box global optimization: Part B
2021
IEEE Transactions on Evolutionary Computation
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The first part covered two major algorithmic approaches to large-scale optimization, namely decomposition methods and hybridization methods such as memetic algorithms and local search. ...
This paper is the second part of a two-part survey series on large-scale global optimization. ...
For example, the decomposition-based algorithm proposed by Mei et al. ...
doi:10.1109/tevc.2021.3130835
fatcat:3x5vho5kxfg4tc7zf4zd4c3crm
Mathematical Tools of Soft Computing
2014
Mathematical Problems in Engineering
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Together with the filter method, an improved filter algorithm with decomposition strategy is proposed for solving nonlinear complementarity problem. ...
The job dispatching problem in a wafer fabrication factory is investigated in the paper "A novel fuzzy-neural slackdiversifying rule based on soft computing applications for job dispatching in a wafer ...
Acknowledgments We wish to express our sincere appreciation to the authors for their excellent contributions. The hard work of all reviewers is greatly acknowledged. ...
doi:10.1155/2014/904014
fatcat:gs4ugjintbf5xopjwjq34tx5sq
A Gradient Multiobjective Particle Swarm Optimization
[chapter]
2018
Optimization Algorithms - Examples
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An adaptive gradient multiobjective particle swarm optimization (AGMOPSO) algorithm, based on a multiobjective gradient (MOG) method, is developed to improve the computation performance. ...
Finally, with regard to the computation performance, the proposed AGMOPSO algorithm is compared with some other multiobjective particle swarm optimization (MOPSO) algorithms and two state-of-the-art multiobjective ...
Based on the theoretical analysis and the experimental results, the proposed AGMOPSO algorithm with the local search strategy MOG is a novel method for solving theses MOPs. ...
doi:10.5772/intechopen.76306
fatcat:5l5ukktm2rhvzaqpqjb3w4urci
Evolutionary Neural Architecture Search and Its Applications in Healthcare
2024
CMES - Computer Modeling in Engineering & Sciences
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Evolutionary algorithms (EAs) for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures. ...
While existing reviews have mainly focused on different strategies to complete NAS, a few studies have explored the use of EAs for NAS. ...
Acknowledgement: The authors wish to express their appreciation to the reviewers for their helpful suggestions which greatly improved the presentation of this paper. ...
doi:10.32604/cmes.2023.030391
fatcat:kozdqzf6avgjdeei3bpvmjfela
Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies
2019
Mathematical Problems in Engineering
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evolutionary algorithm based on decomposition (MOEA/D), a popular framework for multiobjective optimization. ...
Based on the smart and distinct features of IWO and MOEA/D, we introduce multiobjective invasive weed optimization algorithm based on decomposition, abbreviated as MOEA/D-IWO, and try to combine their ...
We first adapt IWO for multiobjective optimization and then integrate it into MOEA/D providing a decomposition-based multiobjective optimization algorithm with invasive weed colonies. ...
doi:10.1155/2019/6943921
fatcat:ploy54foabg4dppgoxeus62umm
Multiobjective Optimal Control for Hydraulic Turbine Governing System Based on an Improved MOGWO Algorithm
2019
Complexity
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In order to optimize the solution to the multiobjective problems, a novel multiobjective grey wolf optimizer algorithm with searching factor (sMOGWO) is also proposed with two improvements: adding searching ...
And then, the sMOGWO is applied to optimize the solutions of the multiobjective problems of HTGS, while different algorithms are employed for comparison. ...
Secondly, a novel MOGWO algorithm based on searching factor (sMOGWO) is proposed to optimize the multiobjective problem. ...
doi:10.1155/2019/3745924
fatcat:f5parawhmvbb7m2ofqigsa2lkq
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