Wednesday, 15:15 - 15:40 h, Room: H 2053


Evrim Dalkiran
RLT-POS: Reformulation-linearization technique-based optimization software for polynomial programming problems

Coauthor: Hanif D. Sherali



We introduce a Reformulation-Linearization Technique (RLT)-based open-source optimization software for solving polynomial programming problems (RLT-POS). We present algorithms and mechanisms that form the backbone of RLT-POS, including grid-bound-factor constraints and semidefinite cuts, constraint filtering techniques, reduced RLT representations, and bound tightening procedures. When implemented individually, each model enhancement has been shown to significantly improve the performance of the standard RLT procedure. When implemented simultaneously, the coordination between model enhancement techniques becomes critical for an improved performance since special structures in the original formulation may be thus affected. More specifically, we discuss the coordination between (a) bound-grid-factor constraints and semidefinite cuts and (b) constraint filtering techniques and reduced RLT representations. We present computational results using instances from the literature as well as randomly generated problems to demonstrate the improvement over a standard RLT procedure, and we compare the performances of the software packages BARON, SparsePOP, and Couenne with RLT-POS.


Talk 1 of the invited session Wed.3.H 2053
"Nonconvex optimization: Theory and algorithms" [...]
Cluster 9
"Global optimization" [...]


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