Accession Number:

AD1030295

Title:

TARCMO: Theory and Algorithms for Robust, Combinatorial, Multicriteria Optimization

Descriptive Note:

Technical Report,15 May 2013,12 May 2016

Corporate Author:

KAISERSLAUTERN UNIV (GERMANY F R) KAISERSLAUTERN Germany

Personal Author(s):

Report Date:

2016-11-28

Pagination or Media Count:

29.0

Abstract:

This project has completed. The PI considered optimization problems with uncertainty in the data. Specifically, algorithms and analysis methods were developed for several optimization scenarios where the random parameters were coming from some unknown probability distribution. One notable result efficiently calculates the average optimal solution for a combinatorial regret problem and provides new bounds for how for this may be from the worst case. For details, see the final report. Further, the project produced 8 published papers and 4 more under review or preparation. The specifics of these references are included in uploaded final report. This work has help to advance the state-of-the-art in robust optimization.

Subject Categories:

  • Operations Research
  • Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE