@inproceedings{e846e063c7ab49f3b6209b5e47ff66cf,
title = "Compact relaxations for polynomial programming problems",
abstract = "Reduced RLT constraints are a special class of Reformulation-Linearization Technique (RLT) constraints. They apply to nonconvex (both continuous and mixed-integer) quadratic programming problems subject to systems of linear equality constraints. We present an extension to the general case of polynomial programming problems and discuss the derived convex relaxation. We then show how to perform rRLT constraint generation so as to reduce the number of inequality constraints in the relaxation, thereby making it more compact and faster to solve. We present some computational results validating our approach.",
keywords = "MINLP, RLT, convex relaxation, nonconvex, polynomial, reformulation, sBB",
author = "Sonia Cafieri and Pierre Hansen and Lucas L{\'e}tocart and Leo Liberti and Fr{\'e}d{\'e}ric Messine",
year = "2012",
month = aug,
day = "1",
doi = "10.1007/978-3-642-30850-5\_8",
language = "English",
isbn = "9783642308499",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "75--86",
booktitle = "Experimental Algorithms - 11th International Symposium, SEA 2012, Proceedings",
note = "11th International Symposium on Experimental Algorithms SEA 2012 ; Conference date: 07-06-2012 Through 09-06-2012",
}