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Optimizing Production using PSO algorithm

Introduction

This project implements a Monte Carlo simulation using triangular membership functions and a Particle Swarm Optimization (PSO) algorithm to find optimal solutions for cost parameters.

Dependencies

  • Python 3.x
  • NumPy
  • Matplotlib

Project Details

Components

  1. Triangular Membership Function: Defines and plots membership functions for given cost parameters.
  2. Monte Carlo Simulation: Simulates defuzzified values for given cost ranges using the triangular membership functions.
  3. Particle Swarm Optimization (PSO): Optimizes cost values using the defuzzified results from the Monte Carlo simulation.

Output

  1. The defuzzified values for COST1 and COST2.
  2. The optimized results from the PSO algorithm.
  3. The average and best fitness values.
  4. The corresponding s1 and s2 values.