Search Results - "Dynamic multi-objective evolutionary algorithms"

Dynamic multi-objective evolutionary algorithms in noisy environments by Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“…Real-world multi-objective optimization problems encounter different types of uncertainty that may affect the quality of solutions. One common type is the…”
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Dynamic multi-objective evolutionary algorithms for single-objective optimization by Jiao, Ruwang, Zeng, Sanyou, Alkasassbeh, Jawdat S., Li, Changhe

“…). The method converts a SOP to an equivalent dynamic multi-objective optimization problem (DMOP). A new dynamic multi-objective evolutionary algorithm…”
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Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms by Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“…Characterization of dynamism is an essential phase for some of the dynamic multi-objective evolutionary algorithms (DMOEAs…”
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Dynamic Multi-Objective Evolutionary Algorithms: An Overview by Guerrero-Peña, Elaine, Araújo, Aluízio, Garrozi, Cícero

“…Evolutionary algorithms have been widely explored and applied in optimization problems. The introduction of multi-objective evolutionary algorithms (MOEAs) has…”
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A general framework based on dynamic multi-objective evolutionary algorithms for handling feature drifts on data streams by Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“… The first building block of the framework is a dynamic multi-objective evolutionary algorithm called Dynamic Filter-Based Feature Selection (DFBFS…”
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Solving the rotating seru production problem with dynamic multi-objective evolutionary algorithms by Liu, Feng, Fang, Kan, Tang, Jiafu, Yin, Yong

“…Today's volatile market conditions in electronic industries have lead to a new production system, seru (which is the Japanese pronunciation for cell), and has…”
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Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing by 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 by 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 front (POF…”
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Dynamic multi-objective workflow scheduling for combined resources in cloud by 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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Preference Integration in Progressive Dynamic Multi-Objective Evolutionary Algorithms by Newton, David William

“… Dynamic multi-objective evolutionary algorithms (DMOEAs) provide an efficient and effective means to address these problems, but the majority of research in this area…”
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Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem by Sahmoud, Shaaban, Topcuoglu, Haluk Rahmi

“… We utilize a dynamic multi-objective evolutionary algorithm to continuously search for the updated set of relevant features after the occurrence of every change in the environment…”
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Modeling an agent-based cooperative dynamic behavior in an uncertain context of SME's sustainable supply chain by 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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Dynamic multi-objective evolutionary algorithm based on knowledge transfer by Wu, Linjie, Wu, Di, Zhao, Tianhao, Cai, Xingjuan, Xie, Liping

“… However, if all individuals are transferred, they may experience negative transfers. Therefore, this paper proposes a novel knowledge transfer method for the dynamic multi-objective evolutionary algorithm (T-DMOEA…”
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A dynamic multi-objective evolutionary algorithm based on intensity of environmental change by Hu, Yaru, Zheng, Jinhua, Zou, Juan, Yang, Shengxiang, Ou, Junwei, Wang, Rui

“…•This paper introduced U-test mechanism to test decision variable and market them into macro-changing decision and micro-changing decision.•An effective update…”
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A dynamic multi-objective evolutionary algorithm using a change severity-based adaptive population management strategy by Azzouz, Radhia, Bechikh, Slim, Said, Lamjed Ben

“…In addition to the need for simultaneously optimizing several competing objectives, many real-world problems are also dynamic in nature. These problems are…”
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A dynamic multi-objective evolutionary algorithm based on Mahalanobis distance and intra-cluster individual correlation rectification by Ge, Fangzhen, Hou, Xing, Chen, Debao, Shen, Longfeng, Liu, Huaiyu

“…). Although many dynamic multi-objective evolutionary algorithms (DMOEAs) have demonstrated impressive performance, there is still room for improvement in accurately predicting population behavior…”
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A dynamic multi-objective evolutionary algorithm based on genetic engineering and improved particle swarm prediction strategy by Yang, Yue, Ma, Yongjie, Zhao, Yan, Zhang, Wenping, Wang, Yu

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A dynamic multi-objective evolutionary algorithm based on gene sequencing and gene editing by Yang, Yue, Ma, Yongjie, Wang, Minghao, Wang, Peidi

“… Inspired by the fact that gene sequencing can discover biological gene defects, this paper proposes a dynamic multi-objective evolutionary algorithm based on gene sequencing and gene editing (GSGE…”
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Antenna design using dynamic multi-objective evolutionary algorithm by Jiao, Ruwang, Sun, Yongzhi, Sun, Jianqing, Jiang, Yuhong, Zeng, Sanyou

“…To enhance the robustness and stability of the antenna design, a novel methodology is presented for modelling the antenna design problem as the constrained…”
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A self-evolving fuzzy system online prediction-based dynamic multi-objective evolutionary algorithm by Sun, Jing, Gan, Xingjia, Gong, Dunwei, Tang, Xiaoke, Dai, Hongwei, Zhong, Zhaoman

“… However, the previous dynamic multi-objective evolutionary algorithms usually use linear prediction models to generate the initial population in the new environment, and some nonlinear prediction…”
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