Two linear approximation algorithms for convex mixed integer nonlinear programming

We present two new algorithms for convex Mixed Integer Nonlinear Programming (MINLP), both based on the well known Extended Cutting Plane (ECP) algorithm proposed by Weterlund and Petersson. Our first algorithm, Refined Extended Cutting Plane (RECP), incorporates additional cuts to the MILP relaxati...

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Vydané v:Annals of operations research Ročník 316; číslo 2; s. 1471 - 1491
Hlavní autori: Melo, Wendel, Fampa, Marcia, Raupp, Fernanda
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.09.2022
Springer
Springer Nature B.V
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ISSN:0254-5330, 1572-9338
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Shrnutí:We present two new algorithms for convex Mixed Integer Nonlinear Programming (MINLP), both based on the well known Extended Cutting Plane (ECP) algorithm proposed by Weterlund and Petersson. Our first algorithm, Refined Extended Cutting Plane (RECP), incorporates additional cuts to the MILP relaxation of the original problem, obtained by solving linear relaxations of NLP problems considered in the Outer Approximation algorithm. Our second algorithm, Linear Programming based Branch-and-Bound (LP-BB), applies the strategy of generating cuts that is used in RECP, to the linear approximation scheme used by the LP/NLP based Branch-and-Bound algorithm. Our computational results show that RECP and LP-BB are highly competitive with the most popular MINLP algorithms from the literature, while keeping the nice and desirable characteristic of ECP, of being a first-order method.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-020-03722-5