Software & Data Downloads — OptimalRML

Optimal Recursive McCormick Linearization of MultiLinear Programs for computing a minimum-sized RML and a size-constrained best-bound RML.

OptimalRML provides Python codes for computing the Optimal Recursive McCormick Linearization (RML) of MultiLinear Programs (MLPs). Given a MLP, the codes can compute: (i) a minimum-sized RML and (ii) a size-constrained best-bound RML. The RMLs define relaxations of MLPs that can be used in global optimization.

  •  Raghunathan, A., Cardonha, C., Bergman, D., Nohra, C.J., "Recursive McCormick Linearization of Multilinear Programs", INFORMS J Computing, DOI: 10.1287/​ijoc.2023.0390, Vol. 37, No. 6, pp. 1650-1669, June 2025.
    BibTeX TR2025-098 PDF Software
    • @article{Raghunathan2025jun,
    • author = {Raghunathan, Arvind and Cardonha, Carlos and Bergman, David and Nohra, Carlos J.},
    • title = {{Recursive McCormick Linearization of Multilinear Programs}},
    • journal = {INFORMS J Computing},
    • year = 2025,
    • volume = 37,
    • number = 6,
    • pages = {1650--1669},
    • month = jun,
    • doi = {10.1287/ijoc.2023.0390},
    • url = {https://www.merl.com/publications/TR2025-098}
    • }

Access software at https://github.com/merlresearch/OptimalRML.