Title
Synthetic Optimization Problem Generation: Show Us The Correlations!
Keywords
0-1 knapsack problem; Capital budgeting problem; Correlation; Generalized assignment problem; Random variable generation; Set-covering problem
Abstract
In many computational experiments, correlation is induced between certain types of coefficients in synthetic (or simulated) instances of classical optimization problems. Typically, the correlations that are induced are only qualified-that is, described by their presumed intensity. We quantify the population correlations induced under several strategies for simulating 0-1 knapsack problem instances and also for correlation-induction approaches used to simulate instances of the generalized assignment, capital budgeting (or multidimensional knapsack), and set-covering problems. We discuss implications of these correlation-induction methods for previous and future computational experiments on simulated optimization problems. © 2009 INFORMS.
Publication Date
6-1-2009
Publication Title
INFORMS Journal on Computing
Volume
21
Issue
3
Number of Pages
458-467
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1287/ijoc.1090.0330
Copyright Status
Unknown
Socpus ID
68749116387 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/68749116387
STARS Citation
Reilly, Charles H., "Synthetic Optimization Problem Generation: Show Us The Correlations!" (2009). Scopus Export 2000s. 11834.
https://stars.library.ucf.edu/scopus2000/11834