Abstract
The paper presents the application of the Monte Carlo annealing method for machine design optimization. The method generates the finite inhomogeneous Markov chain in the space of discrete design parameters with the transition probability dependent on the objective function and given by the Boltzmann-Gibbs distribution of equilibrium statistical mechanics. In this approach the search for the global minimum is simulated by a relaxation towards an equilibrium of the thermodynamic system with the energy proportional to an objective function. The method is applied for the cost optimization of a speed reductor. The performance and prospects of the method for machine design optimization are discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 193-203 |
| Number of pages | 11 |
| Journal | Engineering Optimization |
| Volume | 15 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 May 1990 |
Keywords
- Discrete optimization
- Monte Carlo method
- annealing algorithm
- machine design
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Applied Mathematics