Simulated annealing for single minimum optimization problems

Abstract

Two examples are presented which show that simulated annealing can perform better than quenching and steepest descent even on problems with a single minimum. An implication for real global optimization problems is that simulated annealing can be useful even on time scales which are short compared to the time required for a greedy algorithm to reach the nearest local minimum.

Keywords:

• Simulated annealing
• steepest descent
• stochastic optimization
• greedy algorithms
• global optimization

^∗Permanent address: Department of Mathematical Sciences, San Diego State University, San Diego, CA 92182, USA.

^∗Permanent address: Department of Mathematical Sciences, San Diego State University, San Diego, CA 92182, USA.

Notes

^∗Permanent address: Department of Mathematical Sciences, San Diego State University, San Diego, CA 92182, USA.