Publication Type
Conference Paper
Version
submittedVersion
Publication Date
7-2011
Abstract
We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.
Keywords
Genetic Algorithms, Evolutionary Algorithms, Scheduling
Discipline
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Publication
MIC 2011: Ninth Meta-heuristics International Conference, 25-28 July 2011
First Page
1
Last Page
10
Publisher
MIC
City or Country
Udine, Italy
Citation
Kimbrough, Steven O.; KUO, Ann; and LAU, Hoong Chuin.
Finding robust-under-risk solutions for flowshop scheduling. (2011). MIC 2011: Ninth Meta-heuristics International Conference, 25-28 July 2011. 1-10.
Available at: https://ink.library.smu.edu.sg/sis_research/1387
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Artificial Intelligence and Robotics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons