Strengthening Convex Relaxations of Mixed Integer Non Linear Programming Problems with Separable Non Convexities
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| Názov: | Strengthening Convex Relaxations of Mixed Integer Non Linear Programming Problems with Separable Non Convexities |
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| Autori: | Claudia D'Ambrosio Antonio Frangioni Claudio Gentile |
| Zdroj: | XIII Global Optimization Workshop GOW'16, pp. 49–52, Braga, 4-8/9/2016 info:cnr-pdr/source/autori:Claudia D'Ambrosio Antonio Frangioni Claudio Gentile/congresso_nome:XIII Global Optimization Workshop GOW'16/congresso_luogo:Braga/congresso_data:4-8%2F9%2F2016/anno:2016/pagina_da:49/pagina_a:52/intervallo_pagine:49–52 |
| Informácie o vydavateľovi: | 2016. |
| Rok vydania: | 2016 |
| Predmety: | Global optimization algorithm, Perspective reformulation, Separable functions |
| Popis: | In this work we focus on methods for solving mixed integer non linear programming problems with separable non convexities. In particular, we propose a strengthening of a convex mixed integer non linear programming relaxation based on perspective reformulations. The relaxation is a subproblem of an iterative global optimization algorithm and it is solved at each iteration. Computational results confirm that the perspective reformulation outperforms the standard solution approaches. |
| Druh dokumentu: | Conference object |
| Jazyk: | English |
| Prístupová URL adresa: | http://www.cnr.it/prodotto/i/370618 https://publications.cnr.it/doc/370618 |
| Prístupové číslo: | edsair.cnr...........a72b4b18d24b1e1ab9051a18b89a4b9f |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | In this work we focus on methods for solving mixed integer non linear programming problems with separable non convexities. In particular, we propose a strengthening of a convex mixed integer non linear programming relaxation based on perspective reformulations. The relaxation is a subproblem of an iterative global optimization algorithm and it is solved at each iteration. Computational results confirm that the perspective reformulation outperforms the standard solution approaches. |
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