Optimization and Control Problems in Large-Scale Systems

Kulikowski, Roman; Kruś, Lech; Mańczak, K.; Straszak, A.

doi:10.1016/s1474-6670(17)67539-6

Cited by 3 publications

(3 citation statements)

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“…A suggestion that information value can better be characterized by a multi-component vector of attributes than by a scalar value arose in late 60-ths of the 20 th century (Kulikowski, 1969). In such case, the following problems arose: 1 st , what information (or data, as its particular form) attributes should be taken into account for its value characterization, 2 nd , what does it mean that a multi-aspect information value is "better" or "higher" than another one, 3 rd , how simple data multi-aspect values can be extended on higher-level data structures.…”

Section: A Historical View On the Dq Concepts' Developmentmentioning

confidence: 99%

Data Quality Assessment

Kulikowski

2014

International Journal of Organizational and Collective Intelligence

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A state-of-the-art in the domain of data quality assessment and maintaining in modern information systems is presented in the paper. A short historical view on the development of this problem is given. Particular attention is paid to the development of the idea of multi-aspect data quality assessment. The problem of extension of single data quality assessment on higher-level data structures is considered. The methods of multi-aspect data quality measures ordering for comparison is analyzed and its solution based on the concept of semi-ordering in linear vector (Kantorovitsh) space is proposed. Remarks on organizational and technological tools for data quality maintenance in organizations are given. Expected future trends in the development of data quality assessment and maintenance methods are suggested.

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Section: A Historical View On the Dq Concepts' Developmentmentioning

confidence: 99%

Data Quality Assessment

Kulikowski

2014

International Journal of Organizational and Collective Intelligence

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“…In this method the solution of Af is sought by maximizing the global objective function iteratively, first over the controls m, then over the inputs and outputs z and x3 then again over m and so on until convergence. This is essentially Geoffrion's (1970) method of projection, Mesarovic et al ' s (1970) method of model coordination and what Kulikowski, Krus, Manczak & Straszak (1975) and Wilson (1977) call parametric decomposition. To analyse the conditions under which the method will work it is necessary to describe it more formally which we may do as follows.…”

Section: (B) Primal Coordinationmentioning

confidence: 99%

“…It is quite possible for a subsystem to have more inputs and outputs than controls and thus if the inputs and outputs are arbitrarily fixed it is likely that there are no feasible values of m i which can achieve satisfaction of the local constraints (7). This is part of the reason for introducing the set V into CP but the simple definition of V given in ( 9) belies the fact that it is very difficult to compute this set at the coordinator level without centralizing all the local information (Findeisen 1974^), although some resolution of this difficulty is possible if all the functions T i and hi are linear (Kulikowski et a l . 1975 Another source of difficultyis that, in general, the gradient of the objective function ft(z, x) is not easy to compute and may not even exist: this is an important limitation because one itera tion of the coordinator problem requires solution of N problems P(i).…”

Section: (B) Primal Coordinationmentioning

confidence: 99%

Analysis of complex systems

White

Simmons

1977

Phil. Trans. R. Soc. Lond. A

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It is argued that a complex system of the kind arising in industry is intrinsically structured: that is to say it may be regarded as an interconnected assembly of subsystems. By exploiting this structure it is possible to decompose the problem of controlling a complex system into a series of interlinked subproblems of manageable size. Each subproblem can be solved largely independently of the others, with the interconnections between the subproblems being accounted for by some kind of coordination procedure. Such an approach to complex systems analysis leads naturally to a study of decentralized and hierarchical control methods and as there is no doubt that industrial management has a hierarchical structure it is important to assess the usefulness of the techniques of hierarchical systems theory in the management of complex industrial systems. In cases where the overall management problem can be posed as a linear or non-linear programming problem there is a good body of theory to support the decentralized approach and the basic concepts of this theory are illustrated in this paper by consideration of decentralized optimization of an interconnected production system. It is shown that effective optimal coordination of such a system is difficult to achieve if the subsystems are nonlinear but that satisfactory coordination procedures may be devised if proper account is taken of the slackness which usually exists in the interconnections between real systems. The need to assess the usefulness of these ideas in a real industrial environment is stressed.

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Multilevel structures for control systems

Findeisen

New Trends in Systems Analysis

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Optimization and Control Problems in Large-Scale Systems

Cited by 3 publications

References 1 publication

Data Quality Assessment

Data Quality Assessment

Analysis of complex systems

Multilevel structures for control systems

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