
Accession Number : AD0714832
Title : A Mathematical Programming Approach to Identification and Optimization of Complex Systems,
Corporate Author : CALIFORNIA UNIV LOS ANGELES WESTERN MANAGEMENT SCIENCE INST
Personal Author(s) : Holloway,Charles A.
Report Date : AUG 1970
Pagination or Media Count : 48
Abstract : Complex systems are often represented using models which are not traditional, closedform mathematical expressions. Such a model is essentially unknown from the standpoint of a mathematical programming algorithm because the information which is important to the algorithm is only available through experimentation. Extension of mathematical programming to complex systems in which the cost of information is significant leads to combining system identification with optimization. Inner linearization result in computational approaches which combine identification and optimization. The pricing problem associated with restriction when inner linearization is applied selectively is derived using the KuhnTucker conditions. Three approaches to the identificationoptimization problem are proposed: inner linearization followed by restriction (ILR); outer linearization followed by relaxation (OLR); and a sequential combination of inner and outerlinearized subproblems (SIO). Computational experience showed that (ILR) is dominated by (OLR) and (SIO), and that (SIO) is slightly better than (OLR) for some problems. A 'natural' termination rule was evaluated and shown to be significantly inferior to an ex post facto 'optimal' rule. (Author)
Descriptors : (*MATHEMATICAL POGRAMMING, MATHEMATICAL MODELS), CONVEX SETS, MATRICES(MATHEMATICS), ALGORITHMS, INTERATIONS, BOUNDARY VALUE PROBLEMS, OPTIMIZATION
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE