title: Complex production systems' performance measurement: Estimation of aggregate indices under uncertainty
metadata.name: dc.contributor.author
metadata.value: Hovanov, Nikolai V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Fedotov, Yuri V.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2013-12-20T12:11:49Z
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2014-03-17T05:42:28Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2013-12-20T12:11:49Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2014-03-17T05:42:28Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2006
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/834
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/834
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The paper deals with approaches utilized for adjustment of well known Method of Aggregate Indices (MAI) to uncertainty conditions. The necessity for such adjustments occurs because of the shortage of numeric information. It appears at any stage of estimation of the aggregate quality index for operating electricity units when respective measure (index) integrates a system of object's parameters. Each parameter is required for ultimate quality appraisal, and taken together they are supposed to be sufficient for estimating quality level of the analyzed unit. The Baye's uncertainty randomization procedure is proposed as a tool to simulate the shortage of numeric information. Through this procedure separate indices, weight coefficients and aggregated indices are transformed into correspondent random magnitudes. Then, comparing the qualities of any two objects is converted in the problem of revealing a certain type of stochastic dominance between respective randomized aggregate indices. The software implementation of described above method of Randomized Aggregated Indices Method (RAIM) is based on discrete model of weight coefficients, which allows for generation of all their possible meanings by directed calibration of all feasible bundles of the coefficients. The software implementation of full calibration of possible values for the aggregate indices permits consideration of additional information supplied by experts. It is shaped as a system of inequalities for feasible values of the weight coefficients. Such nonnumeric information from experts substantially increases the accuracy and reliability of constructed randomized estimates of the objects' aggregate quality indices.
metadata.lang: ru
metadata.name: dc.language.iso
metadata.value: Russian
metadata.lang: ru
metadata.name: dc.publisher
metadata.value: Graduate School of Management, Saint Petersburg State University
metadata.lang: -
metadata.name: dc.relation.ispartofseries
metadata.value: Discussion Paper; #28(R)-2006
metadata.lang: -
metadata.name: dc.title
metadata.value: Complex production systems' performance measurement: Estimation of aggregate indices under uncertainty
metadata.lang: ru
metadata.name: dc.title.alternative
metadata.value: Модели учета неопределенности при построении сводных показателей эффективности деятельности сложных производственных систем
metadata.lang: -
metadata.name: dc.type
metadata.value: Working Paper
metadata.lang: ru
metadata.name: dc.contributor.altauthor
metadata.value: Хованов, Н. В.
metadata.lang: -
metadata.name: dc.contributor.altauthor
metadata.value: Федотов, Ю. В.
metadata.lang: -
resources.filename: 28(R)_2006.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/834/1/28%28R%29_2006.pdf
resources.format: Adobe PDF
resources.size: 1,13 MB