Particle Swarm Optimization (PSO) Algorithm Implementation

Function description: A complete n-iterations Particle Swarm Optimization (PSO) algorithm process that returns the minimum and maximum average fitness values obtained during execution, along with online performance and offline performance data. [Result,OnLine,OffLine,MinMaxMeanAdapt]=PsoProcess(SwarmSize,ParticleSize,ParticleScope,InitFunc,StepFindFunc,AdaptFunc,IsStep,IsDraw,LoopCount,IsPlot) Input parameter: SwarmSize: Number of particles in the population (swarm size) Input parameter: ParticleSize: Dimensionality of each particle (number of variables) Input parameter: ParticleScope: Operation range for each dimension of particles; ParticleScope format: 3-dimensional particle ParticleScope format: [x1Min,x1Max x2Min,x2Max x3Min,x3Max] Input parameter: InitFunc: Particle swarm initialization function - handles initial position and velocity setup Input parameter: StepFindFunc: Single-step velocity and position update function - implements PSO movement equations Input parameter: AdaptFunc: Fitness evaluation function - calculates objective function values Input parameter: IsStep: Whether to pause after each iteration; IsStep=0, no pause; otherwise pause. Default is no pause Input parameter: IsDraw: Whether to visualize iteration process graphically; IsDraw=0, no visualization; otherwise graphical representation. Default is no visualization Input parameter: LoopCount: Number of iterations; default is 100 iterations Input parameter: IsPlot: Controls whether to plot online and offline performance graphs; IsPlot=0, no display; IsPlot=1; display graphical results. Default IsPlot=1 Return value: Result represents the optimal solution obtained after iterations Return value: OnLine contains online performance data (tracking fitness during optimization) Return value: OffLine contains offline performance data (tracking best-so-far fitness) Return value: MinMaxMeanAdapt contains the minimum and maximum average fitness values obtained during the complete iteration process Usage: [Result,OnLine,OffLine,MinMaxMeanAdapt]=PsoProcess(SwarmSize,ParticleSize,ParticleScope,InitFunc,StepFindFunc,AdaptFunc,IsStep,IsDraw,LoopCount,IsPlot); Exception handling: First ensure this file is in Matlab's search path, then check relevant prompt messages. Note: Please ensure this file is included in Matlab's search path, otherwise relevant error messages will appear. The algorithm implements standard PSO with customizable initialization, update rules, and fitness functions for flexible optimization problem solving.