Rapid Solutions to Hard Problems Using Fast Messy Genetic Algorithms

reportActive / Technical Report | Accession Number: ADA332334 | Open PDF

Abstract:

This project developed and applied a type of non-traditional genetic algorithm called a fast messy genetic algorithm fmGA. Critical bounding theory and computational experiments show that fmGAs converge to high quality solutions with high probability in times that grow no faster than a sub quadratic function of the number of decision variables. These results have important ramifications for the design and operation of the next generation of Air Force systems.

Author(s):
Goldberg, David E.
Author Organization(s):
ILLINOIS UNIV AT URBANA DEPT OF GENERALENGINEERING
Descriptive Note:
Final rept. 1 Jan 94-30 Sep 96
Pagination:
0008

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
X0003, AFOSR-TR-97-0652
Contract/Grant Number(s):
F49620-94-1-0103
Monitor Series:
TR-97-0652, AFOSR
 Subject Terms
Joint Capability Areas:
JCA_1.2.3_Educating; JCA_4.6_Engineering; JCA_5_Command and Control
Modernization Areas:
AI and Machine Learning
Communities of Interest:
Autonomy
Descriptor(s):
*ALGORITHMS, MATHEMATICAL MODELS, OPTIMIZATION, COMPUTER PROGRAMMING
Field(s)/Group(s):
Computer Programming and Software
Keyword(s):
GENETIC ALGORITHMS, EVOLUTIONARY PROGRAMMING
Report Date:
1997 Feb 25
Creation Date:
1997 Dec 17