Results 11 to 20 of about 172,422 (234)
International Journal of Computational Intelligence SystemsIn metaheuristic multi-objective optimization, the term effectiveness is used to describe the performance of a metaheuristic algorithm in achieving two main goals—converging its solutions towards the Pareto front and ensuring these solutions are well ...
Kanak Kalita +4 more
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A Multiobjective Framework for Many-Objective Optimization [PDF]
IEEE Transactions on Cybernetics, 2022 It is known that many-objective optimization problems (MaOPs) often face the difficulty of maintaining good diversity and convergence in the search process due to the high-dimensional objective space. To address this issue, this article proposes a novel multiobjective framework for many-objective optimization (Mo4Ma), which transforms the many ...
Si-Chen Liu +3 more
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Merge Nondominated Sorting Algorithm for Many-Objective Optimization [PDF]
IEEE Transactions on Cybernetics, 2021 Many Pareto-based multi-objective evolutionary algorithms require to rank the solutions of the population in each iteration according to the dominance principle, what can become a costly operation particularly in the case of dealing with many-objective optimization problems.
Javier Moreno +3 more
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Many Objective Bayesian Optimization
, 2021 arXiv admin note: text overlap with arXiv:2101 ...
Martín, Lucia Asencio +1 more
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Many-objective (Combinatorial) Optimization is Easy
Proceedings of the Genetic and Evolutionary Computation Conference, 2023 It is a common held assumption that problems with many objectives are harder to optimize than problems with two or three objectives. In this paper, we challenge this assumption and provide empirical evidence that increasing the number of objectives tends to reduce the difficulty of the landscape being optimized.
Arnaud Liefooghe, Manuel Lopez-Ibanez
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A Many-Objective Marine Predators Algorithm for Solving Many-Objective Optimal Power Flow Problem
Applied Sciences, 2022 Since the increases in electricity demand, environmental awareness, and power reliability requirements, solutions of single-objective optimal power flow (OPF) and multi-objective OPF (MOOPF) (two or three objectives) problems are inadequate for modern ...
Sirote Khunkitti +2 more
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Diversity Assessment in Many-Objective Optimization [PDF]
IEEE Transactions on Cybernetics, 2017 Maintaining diversity is one important aim of multiobjective optimization. However, diversity for many-objective optimization problems is less straightforward to define than for multiobjective optimization problems. Inspired by measures for biodiversity, we propose a new diversity metric for many-objective optimization, which is an accumulation of the ...
Wang, Handing, Jin, Yaochu, Yao, Xin
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Approximation schemes for many-objective query optimization [PDF]
Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, 2014 The goal of multi-objective query optimization (MOQO) is to find query plans that realize a good compromise between conflicting objectives such as minimizing execution time and minimizing monetary fees in a Cloud scenario. A previously proposed exhaustive MOQO algorithm needs hours to optimize even simple TPC-H queries.
Trummer, Immanuel, Koch, Christoph
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Many-objective evolutionary algorithm based on three-way decision
Egyptian Informatics Journal, 2023 In recent years, many-objective optimization problems have been widely used. however, with the increase of the number of objectives, the difficulty of solving increases exponentially, and the imbalance between convergence and diversity becomes more ...
Zhihua Cui +3 more
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MooFuzz: Many-Objective Optimization Seed Schedule for Fuzzer
Mathematics, 2021 Coverage-based Greybox Fuzzing (CGF) is a practical and effective solution for finding bugs and vulnerabilities in software. A key challenge of CGF is how to select conducive seeds and allocate accurate energy. To address this problem, we propose a novel
Xiaoqi Zhao +4 more
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