A twist on SLP algorithms for NLP and MINLP problems: an application to gas transmission networks

作     者：Gonzalez Rueda, Angel M. Gonzalez Diaz, Julio Fernandez de Cordoba, Maria P. 

作者机构：Univ Santiago de Compostela Dept Stat Math Anal & Optimizat Santiago De Compostela Spain ITMATI IMAT Santiago De Compostela Spain MODESTYA Res Grp Santiago De Compostela Spain 

出 版 物：《OPTIMIZATION AND ENGINEERING》 (最优化与工程学)

年 卷 期：2019年第20卷第2期

页      面：349-395页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0701[理学-数学] 

基　　金：Reganosa company ITMATI Ministerio de Economia y Competitividad FEDER [MTM2014-60191-JIN] Xunta de Galicia [ED431C-2017/38] Ministerio de Educacion [FPU13/01130] 

主　　题：Gas transmission networks Optimization Sequential linear programming NLP problems MINLP problems 

摘      要：This paper presents a modification of classic SLP algorithms for the resolution of NLP and MINLP problems, and does it with a clear application in mind: optimization of gas transmission networks. The SLP-NTR and 2-step SLP algorithms we present have been developed within the collaboration with a company of the gas industry and thoroughly tested with real problems in this field. Here we present a comparison of their performance with that of classic SLP algorithms and state of the art solvers. Importantly, to provide some foundations for the potential applicability of these new algorithms to general NLP and MINLP problems, we present a theoretical analysis of their properties.