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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Vydané v:	Applied Mathematical Modelling Ročník 107; s. 256 - 274
Hlavní autori:	Tang, Jiachang, Fu, Chunming, Mi, Chengji, Liu, Haibo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Inc 01.07.2022 Elsevier BV
Predmet:	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
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