Evaluating Solvers for Linearly Constrained Simulation Optimization
Linearly constrained simulation optimization problems are those that include deterministic linear constraints in addition to an objective function that can only be evaluated through simulation. We provide several solvers for linearly constrained simulation optimization that all rely on gradient estimates of the objective function. We compare these solvers on random instances of 4 test problems from SimOpt.
Authors
- Lingling Liu
- Tinghan Ye (ORCID: https://orcid.org/0000-0001-6369-4554)
- Shane G. Henderson (ORCID: https://orcid.org/0000-0003-1004-4034)
- Ruiwen He
- Natthawut Boonsiriphatthanajaroen (ORCID: https://orcid.org/0009-0004-5883-5497)
Institutions
- Cornell University (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838622
- Citations
- 1
- Primary Topic
- Simulation Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.49
Funders
- National Science Foundation