Abstract
In this chapter, the main objective of maximizing the Material Reduction Rate (MRR) in the drilling process is carried out. The model describing the drilling process is adopted from the authors' previous work. With the model in hand, a novel algorithm known as Weightless Swarm Algorithm is employed to solve the maximization of MRR due to some constraints. Results show that WSA can find solutions effectively. Constraints are handled effectively, and no violations occur; results obtained are feasible and valid. Results are then compared to previous results by Particle Swarm Optimization (PSO) algorithm. From this comparison, it is quite impossible to conclude which algorithm has a better performance. However, in general, WSA is more stable compared to PSO, from lower standard deviations in most of the cases tested. In addition, the simplicity of WSA offers abundant advantages as the presence of a sole parameter enables easy parameter tuning and thereby enables this algorithm to perform to its fullest.
| Original language | English |
|---|---|
| Title of host publication | Emerging Research on Swarm Intelligence and Algorithm Optimization |
| Publisher | IGI Global |
| Pages | 181-190 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781466663299 |
| ISBN (Print) | 1466663286, 9781466663282 |
| DOIs | |
| Publication status | Published - 31 Jul 2014 |