Heuristic random optimization

Compared to the widely used gradient-based optimization techniques, random search methods have the advantages of easy computation, simple implementation and global optimality; especially when constraints are involved, or when the gradient is burdensome or impossible to calculate. In this paper, seve...

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Bibliographic Details
Published in:Computers & chemical engineering 1998-01, Vol.22 (3), p.427-444
Main Authors: Li, Junyi, Russell Rhinehart, R.
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Global optimization
Heuristics
Neural networks
Operational research and scientific management
Operational research. Management science
Optimization
Optimization. Search problems
Random optimization
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Summary:Compared to the widely used gradient-based optimization techniques, random search methods have the advantages of easy computation, simple implementation and global optimality; especially when constraints are involved, or when the gradient is burdensome or impossible to calculate. In this paper, several heuristic principles are proposed to enhance the performance of the random optimization. Several examples are used to illustrate the advantages of heuristic random optimization over random and gradient-based methods.
ISSN:0098-1354
1873-4375
DOI:10.1016/S0098-1354(97)00005-7