An interval sequential linear programming for nonlinear robust optimization problems

•An interval sequential linear programming for nonlinear robust optimization is proposed.•An approximate possibility sensitivity is proposed to efficiently obtain the partial derivatives of the constraints.•A novel iterative mechanism is established to improve the convergence rate.•Two numerical exa...

Full description

Bibliographic Details

Published in:	Applied Mathematical Modelling Vol. 107; pp. 256 - 274
Main Authors:	Tang, Jiachang, Fu, Chunming, Mi, Chengji, Liu, Haibo
Format:	Journal Article
Language:	English
Published:	New York Elsevier Inc 01.07.2022 Elsevier BV
Subjects:	Interval uncertainty Iterative methods Linear programming Optimization models Reliability-based possibility degree of interval (RPDI) Robust optimization Robustness (mathematics) Sensitivity analysis Sequential linear programming Interval uncertainty Robust optimization Sensitivity analysis Sequential linear programming Reliability-based possibility degree of interval (RPDI)
ISSN:	0307-904X, 1088-8691, 0307-904X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!