An implementation of the Particle Swarm Optimization (PSO) algorithm [1,2] in Go. PSO is used for problems involving global stochastic optimization of a continuous function (called the objective function). PSO can also be used for discrete optimization problems, but this behaviour is not implemented in the current version of this library.

The library implements a simple PSO which keeps track of a single global best position for the swarm (i.e. no fancy neighborhood strategies etc.) and maintains a constant inertia weight.

It is actually a rewrite of PSO in C for the purpose of learning Go :-)

Install using:

go get github.com/kkentzo/pso.go

The library can be used as shown in the following code snippet:

package main

import (
    "github.com/kkentzo/pso.go"
)

func main() {
    settings := pso.DefaultSettings()
    settings.ObjectiveFunction = pso.Rosenbrock
    swarm := pso.Initialize(settings)
    swarm.Run()
}

• Implement linearly decreasing inertia weight
• Implement neighborhood information strategies
• Investigate particle parallelism using goroutines
• Implement specific settings for objective functions [DONE]
• Add tests!