Výsledky vyhledávání - "dynamic multi-objective evolutionary algorithm"

An ensemble learning based prediction strategy for dynamic multi-objective optimization Autor Wang, Feng, Li, Yixuan, Liao, Fanshu, Yan, Hongyang

“…Prediction strategies are widely-used in dynamic multi-objective evolutionary algorithms (DMOEAs). However, the characteristics of the environmental changes…”
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A dynamic multi-objective optimization evolutionary algorithm with adaptive boosting Autor Peng, Hu, Xiong, Jianpeng, Pi, Chen, Zhou, Xinyu, Wu, Zhijian

“…Dynamic multi-objective optimization problems (DMOPs) are prevalent in the real world, where the challenge in solving DMOPs is how to track the time-varying…”
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Dynamic Multi-objective Optimization Algorithm Based on RNN Information Accumulation Autor CHENG Xuefeng, DONG Minggang

“…Dynamic multi-objective optimization problems exist widely in real life.After the environment changes,it is necessary for the evolutionary algorithm to have…”
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A micro dynamic multi-objective evolutionary algorithm with flexible response strategy Autor Wu, Shi, Peng, Hu, Liu, Zhuo, Liu, Lin, Cao, Lianglin, Wu, Zhijian

“…Resource constraints exist in solving realistic dynamic multi-objective optimization problems (DMOPs), such as those based on low-power microprocessors…”
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An adaptive dynamic multi-objective evolutionary algorithm using two-stage correlation-based decision variable analysis Autor Liu, Tianyu, Xu, Siyue, Wu, Xiangfei

“…In recent years, dynamic multi-objective optimization problems (DMOPs) have received increasing attention, and numerous strategies have emerged to solve such…”
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Application of population evolvability in a hyper-heuristic for dynamic multi-objective optimization Autor Macias-Escobar, Teodoro, Cruz-Reyes, Laura, Dorronsoro, Bernabé, Fraire-Huacuja, Héctor, Rangel-Valdez, Nelson, Gómez-Santillán, Claudia

“…It is important to know the properties of an optimization problem and the difficulty an algorithm faces to solve it. Population evolvability obtains…”
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Diffusion Meets Evolution: Constraint-Guided Learning for Large-Scale Dynamic Multi-Objective Evolutionary Optimization Autor Li, Chenyang, Yen, Gary G., He, Zhenan

“…Large-scale dynamic multi-objective optimization problems (LSDMOPs) are becoming increasingly prevalent in practical scenarios such as logistics planning,…”
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Domain Generalization-Based Evolutionary Algorithm for Hybrid Flowshop Dynamic Scheduling Problem Autor Wang, Hao, Wang, Xingqin, Gu, Xin

“…Hybrid flowshop dynamic scheduling problem (HFDSP) represents an important area of scheduling problems. In real life, machine status may change in the dynamic…”
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UAV online path planning based on dynamic multiobjective evolutionary algorithm Autor Peng Xingguang, Xu Demin, Zhang Fubin

“…Online path planning (OPP) is the basic issue of some complex mission and is indeed a dynamic multi-objective optimization problem (DMOP). In this paper, we…”
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Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing Autor Ismayilov, Goshgar, Topcuoglu, Haluk Rahmi

“…Workflow scheduling is a largely studied research topic in cloud computing, which targets to utilize cloud resources for workflow tasks by considering the…”
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Dynamic multi-objective optimization algorithm based decomposition and preference Autor Hu, Yaru, Zheng, Jinhua, Zou, Juan, Jiang, Shouyong, Yang, Shengxiang

“…Most of the existing dynamic multi-objective evolutionary algorithms (DMOEAs) are effective, which focuses on searching for the approximation of Pareto-optimal…”
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Diffusion Learning-guided Evolution for Large-scale Dynamic Multi-Objective Optimization Autor Li, Chenyang, Yen, Gary G., He, Zhenan

“…Large-scale, dynamic multi-objective optimization problems (LSDMOPs) extend traditional DMOPs into high-dimensional decision spaces, reflecting the growing…”
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A general framework based on dynamic multi-objective evolutionary algorithms for handling feature drifts on data streams Autor Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“…This paper proposes a new and efficient framework to deal with the classification of data streams when exhibiting feature drifts. The first building block of…”
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A dynamic multi-objective evolutionary algorithm based on manifold dimensionality reduction and cluster-guided poly-directional search strategy Autor Hu, Yaru, Yang, Xiao, Fu, Wen, Zheng, Yunfei, Ou, Junwei, Zou, Juan

“…Dynamic multi-objective evolutionary algorithms (DMOEAs) are widely employed to solve dynamic multi-objective optimization problems (DMOPs), yet accurately…”
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Dynamic multi-objective workflow scheduling for combined resources in cloud Autor Zhang, Yan, Wu, Linjie, Li, Mengxia, Zhao, Tianhao, Cai, Xingjuan

“…Cloud resource providers offer idle resources to users as spot instances. The price of the instances changes with market supply and demand, and the dynamic…”
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Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms Autor Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“…Characterization of dynamism is an essential phase for some of the dynamic multi-objective evolutionary algorithms (DMOEAs) in order to improve their…”
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Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem Autor Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“…In this paper, we propose an enhanced feature selection algorithm able to cope with feature drift problem that may occur in data streams, where the set of…”
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Modeling an agent-based cooperative dynamic behavior in an uncertain context of SME's sustainable supply chain Autor Ben Mekki, Aicha, Tounsi, Jihene, Said, Lamjed Ben

“…by drawing upon the concept of competitiveness and the dynamism of the environment, a knowledge base model is developed to design the behavior of autonomous…”
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