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Improve Particle Swarm Optimization and Differential Evolution Algorithms Using Nash Bargaining Theory
Published 2025-04-01“…<p><span style="font-size: 10.0pt; line-height: 125%; font-family: 'Georgia',serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Georgia; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US; mso-fareast-language: JA; mso-bidi-language: AR-SA;"> </span><span style="font-size: 11pt; line-height: 125%; font-family: Calibri, sans-serif;">This article proposes a new approach in solving optimization (issues) problems in which two known optimization algorithm of particle swarm algorithm (PSO) and differential evolution (DE) a cooperate. …”
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HEPSO-SMC: a sliding mode controller optimized by hybrid enhanced particle swarm algorithm for manipulators
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HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction
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Using The Hybrid GA-Ant Algorithm To Find The Optimal Path In Computer Networks
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A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system
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Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation
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Hybrid precoding method for millimeter-wave massive MIMO systems based on IAFS algorithm
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A Hybrid Whale Optimization Approach for Fast-Convergence Global Optimization
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A Hybrid Particle Swarm Optimizer for Curriculum Sequencing Problem
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