Search Results - scalable multiobjective optimization

A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization by Liu, Songbai, Lin, Qiuzhen, Li, Jianqiang, Tan, Kay Chen

“…) for multiobjective optimization problems (MOPs). However, these progressively improved MOEAs have not necessarily been equipped with scalable and learnable problem-solving strategies for new and grand challenges brought by the scaling-up MOPs…”
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Evolutionary Constrained Multiobjective Optimization: Scalable High-Dimensional Constraint Benchmarks and Algorithm by Qiao, Kangjia, Liang, Jing, Yu, Kunjie, Yue, Caitong, Lin, Hongyu, Zhang, Dezheng, Qu, Boyang

“…Evolutionary constrained multiobjective optimization has received extensive attention and research in the past two decades, and a lot of benchmarks have been proposed to test the effect…”
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A Scalable Test Suite for Continuous Dynamic Multiobjective Optimization by Jiang, Shouyong, Kaiser, Marcus, Yang, Shengxiang, Kollias, Stefanos, Krasnogor, Natalio

“…Dynamic multiobjective optimization (DMO) has gained increasing attention in recent years…”
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A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization by Liu, Songbai, Lin, Qiuzhen, Li, Jianqiang, Kay Chen Tan

“…) for multiobjective optimization problems (MOPs). However, these progressively improved MOEAs have not necessarily been equipped with scalable and learnable problem-solving strategies for new and grand challenges brought by the scaling-up MOPs…”
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A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization by Hong, Wenjing, Tang, Ke, Zhou, Aimin, Ishibuchi, Hisao, Yao, Xin

“… from large-scale multiobjective optimization have rarely been studied. In this paper, the exclusive challenges along with the increase of the number of variables of a multiobjective optimization problem (MOP…”
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A novel scalable test problem suite for multimodal multiobjective optimization by Yue, Caitong, Qu, Boyang, Yu, Kunjie, Liang, Jing, Li, Xiaodong

“…This paper proposes a novel scalable multimodal multiobjective test problem suite…”
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Scalable modeling and solution of stochastic multiobjective optimization problems by Cao, Yankai, Fuentes-Cortes, Luis Fabian, Chen, Siyu, Zavala, Victor M.

“… We present a scalable computing framework for the solution stochastic multiobjective optimization problems…”
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Scalable modeling and solution of stochastic multiobjective optimization problems by Cao, Yankai, Fuentes-Cortes, Luis Fabian, Chen, Siyu, Zavala, Victor M.

“…Not provided…”
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Performance Comparison of Multiobjective Evolutionary Algorithms on Problems with Partially Different Properties from Popular Test Suites by Matsumoto, Takashi, Masuyama, Naoki, Nojima, Yusuke, Ishibuchi, Hisao

“…A Multiobjective Evolutionary Algorithm (MOEA) is one of the effective approaches for solving Multiobjective Optimization Problems (MOPs…”
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Multiobjective de novo drug design with recurrent neural networks and nondominated sorting by Yasonik, Jacob

“…Research productivity in the pharmaceutical industry has declined significantly in recent decades, with higher costs, longer timelines, and lower success rates…”
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Adaptive Weighted Aggregation 2: More scalable AWA for multiobjective function optimization by Hamada, Naoki, Nagata, Yuichi, Kobayashi, Shigenobu, Ono, Isao

“…Adaptive Weighted Aggregation (AWA) is a frame work of multi-starting optimization methods based on scalarization for solving multiobjective function optimization problems…”
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Boosting scalability for large-scale multiobjective optimization via transfer weights by Hong, Haokai, Jiang, Min, Yen, Gary G.

“… Second, to boost scalability when solving LSMOPs, we propose a scalable multiobjective optimization algorithm by transferring…”
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Scaling Multiobjective Evolution to Large Data With Minions: A Bayes-Informed Multitask Approach by Chen, Zefeng, Gupta, Abhishek, Zhou, Lei, Ong, Yew-Soon

“… Targeting scalable multiobjective evolution under large-instance data, this article proposes the general idea of using subsampled small-data tasks as helpful minions (i.e…”
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A Review of Features and Limitations of Existing Scalable Multiobjective Test Suites by Zapotecas-Martinez, Saul, Coello Coello, Carlos A., Aguirre, Hernan E., Tanaka, Kiyoshi

“…In multiobjective optimization, a scalable test problem is one that can be formulated for an arbitrary number of objectives…”
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A Scalable Test Suite for Continuous Dynamic Multiobjective Optimisation by Jiang, Shouyong, Kaiser, Marcus, Yang, Shengxiang, Kollias, Stefanos, Krasnogor, Natalio

“…Dynamic multiobjective optimisation has gained increasing attention in recent years…”
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Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search by Suzuki, Takamasa, Ma, Dian, Yasuo, Nobuaki, Sekijima, Masakazu

“… Until now, multiobjective optimization via generative models has often involved linear combinations of different reward functions…”
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Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework by Sarani Rad, Fatemeh, Li, Juan

“… optimization, overlooking factors such as minimizing insulin overuse, reducing glycemic variability, and ensuring patient safety…”
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Cooperative Differential Evolution With an Attention-Based Prediction Strategy for Dynamic Multiobjective Optimization by Liu, Xiao-Fang, Zhang, Jun, Wang, Jun

“…In dynamic multiobjective optimization, the Pareto front (PF) or Pareto set varies over time as the problem environment changes…”
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Heterogeneous Ensemble-Based Infill Criterion for Evolutionary Multiobjective Optimization of Expensive Problems by Guo, Dan, Jin, Yaochu, Ding, Jinliang, Chai, Tianyou

“…Gaussian processes (GPs) are the most popular model used in surrogate-assisted evolutionary optimization of computationally expensive problems, mainly because GPs are able to measure the uncertainty of the estimated fitness…”
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Optimal Sizing of Traction Motors Using Scalable Electric Machine Model by Ramakrishnan, Kesavan, Stipetic, Stjepan, Gobbi, Massimiliano, Mastinu, Gianpiero

“… The method employs a scalable electric machine model inside the multiobjective optimization (MOO) algorithm…”
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