🚀 Multi-Objective KOARIME with (M−1)-GPD Environmental Selection
In this video, we demonstrate how the KOARIME evolutionary algorithm can be extended from a single-objective optimizer into a multi-objective framework using the powerful (M−1)-GPD environmental selection strategy.
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🔹 What you’ll learn in this video:
How KOARIME is adapted for multi-objective optimization
The role of (M−1)-GPD selection in maintaining convergence and diversity
Performance analysis on benchmark problems (DTLZ2 / MaF test suite)
Visualization of Pareto fronts, convergence (HV & IGD), and diversity metrics
📊 This tutorial is perfect for:
PhD researchers in Optimization, AI, and Evolutionary Computation
Students working on Multi-Objective Evolutionary Algorithms (MOEAs)
Practitioners applying Pareto optimization in engineering and data science
🔗 Source Code: Full MATLAB implementation included in the video description.
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multi objective optimization, KOARIME, (M-1)-GPD selection, evolutionary algorithms, Pareto optimization, many-objective optimization, DTLZ2 benchmark, MaF test suite, MATLAB optimization, MATLAB evolutionary algorithm, PhD research projects, hypervolume IGD, optimization algorithms, evolutionary computation, MOEA, MOEA/D, NSGA-II, research tutorial
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Two-Area Load Frequency Control (LFC) using Grey Wolf Fuzzy-PID Controller | MATLAB Simulink Simulation This video presents the modeling and simulation of a Two-Area Power System Load Frequency Control (LFC) using an intelligent hybrid controller — the Grey Wolf Optimization (GWO) tuned Fuzzy-PID Controller implemented in MATLAB/Simulink. The proposed controller improves dynamic performance, frequency stability, and tie-line power oscillation damping compared to conventional PID and Fuzzy controllers. 👨💻 Project Support 🌐 www.matlabprojectscode.com 📧 matlabprojectscode@gmail.com 📱 WhatsApp: +91 8300015425 🔍 Topics Covered Modeling of two-area interconnected thermal power system Governor, turbine, and tie-line power flow representation Fuzzy logic controller for adaptive gain tuning Grey Wolf Optimization (GWO) algorithm for optimal PID parameter selection Simulation of load disturbances and system response Comparison of PID, Fuzzy-PID, and GWO-Fuzzy-PID controllers Performa...
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