Aggregation and Disaggregation Techniques and Methodology in Optimization

A fundamental issue in the use of optimization models is the tradeoff between the level of detail and the ease of using and solving the model. Aggregation and disaggregation techniques have proven to be valuable tools for manipulating data and determining the appropriate policies to employ for this...

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Bibliographic Details
Published in:Operations research 1991-07, Vol.39 (4), p.553-582
Main Authors: Rogers, David F, Plante, Robert D, Wong, Richard T, Evans, James R
Format: Article
Language:English
Subjects:
A posteriori knowledge
A priori knowledge
Aggregation
Aggregations
Algorithms
Applications
Applied sciences
Approximation
approximations/heuristics: large-scale models
cluster analysis: aggregation process
Decision making models
Error bounds
Exact sciences and technology
linear integer: aggregation/disaggregation and surrogate programming
Modeling
Objective functions
Operational research and scientific management
Operational research. Management science
Operations research
Optimization
Optimization. Search problems
Production planning
production/scheduling
programming
statistics
Studies
Techniques
Theory
Transportation
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Summary:A fundamental issue in the use of optimization models is the tradeoff between the level of detail and the ease of using and solving the model. Aggregation and disaggregation techniques have proven to be valuable tools for manipulating data and determining the appropriate policies to employ for this tradeoff. Furthermore, aggregation and disaggregation techniques offer promise for solving large-scale optimization models, supply a set of promising methodologies for studying the underlying structure of both univariate and multivariate data sets, and provide a set of tools for manipulating data for different levels of decision makers. In this paper, we develop a general framework for aggregation and disaggregation methodology, survey previous work regarding aggregation and disaggregation techniques for optimization problems, illuminate the appropriate role of aggregation and disaggregation methodology for optimization applications, and propose future research directions.
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.39.4.553