NDLI: Simultaneous optimisation of both scalar parameters and agent reaction strategies using genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Gibson, G.M.
Copyright Year	1995
Description	Author affiliation: Sch. of Comput. & Inf. Sci., Univ. of South Australia, Pooraka, SA, Australia (Gibson, G.M.)
Abstract	When optimising simulation models of organised systems, it may be necessary to optimise the decision making behaviour of human operators and/or computer controllers, either because the optimal strategies for them to use are not self-evident, or because they are dependent on other variables which are being optimised. In this paper, a new kind of genetic algorithm (GA) is presented which optimises problems containing both traditional scalar parameters and multiple reaction strategies, expressed as agent rule bases. It is a multi-level GA in the sense that the strings may have one or more GAs embedded within them. Its performance on two industrial simulation test problems indicate that it can successfully generate good solutions to problems that have relatively small-scale control strategies to be optimised in conjunction with other parameters.<>
Starting Page	405
Ending Page	410
File Size	553292
Page Count	6
File Format	PDF
ISBN	0780320816
DOI	10.1109/IACC.1995.465806
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-01-05
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Manufacturing industries Industrial control Computational modeling Computer simulation Decision making Humans Electrical equipment industry Australia Genetic algorithms Context modeling
Content Type	Text
Resource Type	Article

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