Title

Global Optimization of Statistical Functions with Simulated Annealing

Document Type

Article

Publication Date

1-1-1994

Department

Management and International Business

Abstract

Many statistical methods rely on numerical optimization to estimate a model's parameters. Unfortunately, conventional algorithms sometimes fail. Even when they do converge, there is no assurance that they have found the global, rather than a local, optimum. We test a new optimization algorithm, simulated annealing, on four econometric problems and compare it to three common conventional algorithms. Not only can simulated annealing find the global optimum, it is also less likely to fail on difficult functions because it is a very robust algorithm. The promise of simulated annealing is demonstrated on the four econometric problems.

Publication Title

Journal of Econometrics

Volume

60

Issue

1-2

First Page

65

Last Page

99