LDRD final report : robust analysis of large-scale combinatorial applications.

Technical Report · Sat Sep 01 00:00:00 EDT 2007

DOI:https://doi.org/10.2172/921748· OSTI ID:921748

Carr, Robert D; Morrison, Todd ^[1]; Hart, William Eugene; Benavides, Nicolas L ^[2]; Greenberg, Harvey J ^[1]; Watson, Jean-Paul; Phillips, Cynthia Ann

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1. University of Colorado, Denver, CO
2. Santa Clara University, Santa Clara, CA

Discrete models of large, complex systems like national infrastructures and complex logistics frameworks naturally incorporate many modeling uncertainties. Consequently, there is a clear need for optimization techniques that can robustly account for risks associated with modeling uncertainties. This report summarizes the progress of the Late-Start LDRD 'Robust Analysis of Largescale Combinatorial Applications'. This project developed new heuristics for solving robust optimization models, and developed new robust optimization models for describing uncertainty scenarios.

• Research Organization: Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 921748
• Report Number(s): SAND2007-5983; TRN: US200806%%28
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
MATHEMATICAL MODELS
DATA COVARIANCES
COMPUTERIZED SIMULATION
CALCULATION METHODS
Information modeling.
Data modeling.
Infrastructure (Economics)
Uncertainty-Mathematical models.
Simulation and Modeling