In the Bio-Inspired Algorithms class, I explored the application of three algorithms—Genetic Algorithm, Simulated Annealing, and Tabu Search—to solve the cutting stock problem (CSP).

The CSP is a classic optimization problem that involves finding the most efficient way to cut materials from available stock sizes to fulfill a given set of orders. Throughout my presentation, I highlighted some of the related works and research that have utilized these bio-inspired algorithms for solving the cutting stock problem. 

my presentation provided an overview of how Genetic Algorithm, Simulated Annealing, and Tabu Search can be applied to solve the cutting stock problem. These bio-inspired algorithms offer powerful optimization techniques that can maximize material utilization, minimize waste, and improve efficiency in cutting operations.

Table of Contents

  • Problem Description
  • none metahuristic Algorithm
  • Variants of CSP
  • Some related works
  • Genetic Algorithm
  • Co-evolutionary Genetic Algorithm
  • Simulated Annealing
  • Tabu Search

Download Slides.