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...

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Veröffentlicht in:	Applied Mathematical Modelling Jg. 107; S. 256 - 274
Hauptverfasser:	Tang, Jiachang, Fu, Chunming, Mi, Chengji, Liu, Haibo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Inc 01.07.2022 Elsevier BV
Schlagworte:	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-Zugang:	Volltext
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