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Business, general

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Multivariate Stratified Sampling by Optimization

Article Abstract:

The need of the Office of Tax Analysis (OTA) and the treasury Department for microdata samples that give precise estimates, but are small enough to be practical, is one example cited of the use of optimal stratification. The IRS's Statistics of Income (SOI) file is also described briefly. The strata boundaries and sampling concepts are presented, and then the solution method. Subgradient optimization (SGO) and minimum squared error (MSE) methods are used and compared. The results are shown in tables and graphs, and are discussed. Future work is laid out, and unanswered questions are listed. The use to insurance companies is mentioned.

Author: Mulvey, J.M.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1983
Mathematical models, Multivariate analysis, Statistics (Data), Cluster analysis, Estimation, Statistics, Sampling, Sampling Error

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An Optimization Model for Production Costing in Electric Utilities

Article Abstract:

Long range planning for electric utilities trades off between fixed costs and operating costs. The production costing problem needs to know how the system will be operated at each demand level. Modeling is very expensive in computer resources, and simple, less expensive techniques assume linear variable production costs and use optimization submodels to develop a system production cost versus output curve. An example is given.

Author: McGinnis, L.F., Ammons, J.C.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1983
Business planning, Strategic Planning, Models, Cost Estimation, Energy, Power Systems, Utilities, Operations Research, Theory

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Large-Scale Portfolio Optimization

Article Abstract:

A practical algorithm for large-scale mean-variance portfolio optimization is presented. An efficient computational approach is emphasized. The structural properties of current portfolio models are exploited. Transaction limits and costs are taken into account. Graphs and tables illustrate computational results.

Author: Perold, A.F.
Publisher: Institute for Operations Research and the Management Sciences
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1984
Portfolio management, Scientific Research

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Subjects list: Management science, Algorithms, Algorithm, Modeling, Data modeling software, Optimization
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