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20 results for “Particle Swarm Optimization”

  • All 20
  • Metaheuristics 7
  • Courses 1
  • Applications 9
  • Machine Learning 2
  • Multiobjective Optimization 2
  • Fuzzy Systems 1
  • Evolutionary Algorithms 1
  • Metaheuristics

    Particle Swarm Optimization in MATLAB

    Implement particle swarm optimization in MATLAB with velocity updates, bounds, inertia damping, constriction coefficients, and a Sphere test problem.

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  • Multiobjective Optimization

    Multi-Objective PSO in MATLAB

    Run multi-objective PSO in MATLAB with an external repository, grid-based leader selection, mutation, and a two-objective test problem.

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  • Metaheuristics

    Particle Swarm Optimization (PSO) in Python

    Run particle swarm optimization in Python with NumPy, a reusable problem dictionary, configurable parameters, and a bounded Sphere example.

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  • Metaheuristics

    Particle Swarm Optimization (PSO) in MATLAB: Video Tutorial

    Learn PSO in three videos, from the update equations to a MATLAB implementation with position bounds, velocity limits, and constriction coefficients.

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  • Applications

    Economic Dispatching using PSO and Nested PSO

    Study economic dispatch in MATLAB with PSO and nested PSO, generator limits, prohibited zones, transmission losses, and plant-selection costs.

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  • Fuzzy Systems

    Evolutionary ANFIS Training in MATLAB

    Train ANFIS parameters in MATLAB with GA or PSO, using multiplier encoding, a training-RMSE objective, and a nonlinear-regression example.

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  • Applications

    p-Hub Location Allocation Problem in MATLAB

    Model hub location and allocation in MATLAB with PSO, discounted inter-hub transport, opening costs, and a variable number of open hubs.

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  • Applications

    Optimal Robot Path Planning Using PSO in MATLAB

    Plan a 2D robot path in MATLAB with PSO, spline handle points, circular obstacles, sampled path lengths, and obstacle-violation penalties.

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  • Applications

    Optimal Inventory Control using PSO in MATLAB

    Plan integer order quantities in MATLAB with PSO or Firefly search, inventory balances, purchasing and holding costs, and storage-capacity penalties.

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  • Machine Learning

    Feature Selection using Metaheuristics and EAs

    Select features for neural-network regression in MATLAB with GA, ACO, SA, PSO, or NSGA-II, including fixed-size and multi-objective formulations.

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  • Applications

    Facility Layout Design using PSO in MATLAB

    Design a facility layout in MATLAB with PSO, block positions and rotations, material-flow costs, clearance gaps, and overlap penalties.

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  • Applications

    Quadratic Assignment Problem (QAP) Using GA, PSO and FA in MATLAB

    Solve a quadratic assignment example in MATLAB with GA, PSO, or Firefly search, including permutation encoding and weighted facility-location costs.

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  • Applications

    Bin Packing Problem using GA, PSO, FA, and IWO

    Solve bin packing in MATLAB with GA, PSO, Firefly, or Invasive Weed Optimization, using a shared separator encoding and capacity penalties.

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  • Applications

    Minimum Spanning Tree using PSO, ICA and FA

    Study graph encoding in MATLAB with PSO, ICA, and Firefly search for a minimum spanning tree, and compare the result with an exact baseline.

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  • Metaheuristics

    YPEA: Yarpiz Evolutionary Algorithms

    Define an optimization problem once in MATLAB and solve it with 15 algorithms through YPEA, with shared variable types, settings, and result histories.

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  • Machine Learning

    Evolutionary Data Clustering in MATLAB

    Cluster data in MATLAB with GA, PSO, or Differential Evolution, using fixed centers or automatic cluster selection through validity indices.

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  • Applications

    Classic and Intelligent Portfolio Optimization in MATLAB

    Explore portfolio optimization in MATLAB with mean-variance, MAD, and CVaR models, plus PSO, ICA, NSGA-II, and SPEA2 implementations.

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  • Metaheuristics

    Firefly Algorithm (FA) in MATLAB

    Run the Firefly Algorithm in MATLAB with distance-based attraction, shrinking random steps, bound handling, and benchmark functions.

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  • Metaheuristics

    Teaching-Learning-based Optimization in MATLAB

    Implement teaching-learning-based optimization in MATLAB with teacher and learner phases, bound handling, and a Sphere test problem.

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  • Metaheuristics

    Biogeography-Based Optimization (BBO) in MATLAB

    Implement biogeography-based optimization in MATLAB with blended migration, mutation, elitism, and a bounded Sphere test problem.

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