Published 2024-01-16
Keywords
- Parametric Vector Optimization Problems (PVOP),
- Domination Cone,
- Perturbation Maps,
- Set-valued Maps,
- Stability Notions
How to Cite
Abstract
Stability analysis for nonlinear programming systems deals with the possible changes of the system parameters and/or equations that maintain the stability of the solutions. It is a crucial requirement to study the nonlinear system and its practical values, specifically the economic impact in most real-world applications. This paper presents some outcomes in connection with stability analysis corresponding to parametric conic vector optimization problems. For these last optimization problems, two novel types of P-Stability maps, which are the P-Stability notion map and the P-Stability perturbation map, are considered based on six kinds of sets: P-feasible set, P-solvability set, the first, second, third, and fourth kinds of P-Stability notion sets with respect to a specific domination cone P. Furthermore, qualitative characteristics of the P-Stability maps under some continuity and convexity assumptions on the objective function are provided and proved. Specifically, the connections between the P-Stability maps and the P-Stability notion set are investigated. Accordingly, these characteristics were extended to the P-perturbation maps. In addition, the idea of Pstability has heavily used in different applications like network privacy, engineering fields, and some business financial models.
References
- Arutyunov AV, Obukhovskii V (2016) 17. Set-valued maps. Upper semicontinuous and lower semicontinuous set-valued maps. In: 17. Set-valued maps. Upper semicontinuous and lower semicontinuous set-valued maps. De Gruyter, pp 109– 120
- Aubin J-P, Frankowska H (2009) Set-Valued Analysis. Springer Science & Business Media
- Auslender A, Teboulle M (2006) Asymptotic Cones and Functions in Optimization and Variational Inequalities. Springer Science & Business Media
- Bazaraa MS, Sherali HD, Shetty CM (2013) Nonlinear Programming: Theory and Algorithms. John Wiley & Sons
- Bokrantz R, Fredriksson A (2017) Necessary and sufficient conditions for Pareto efficiency in robust multiobjective optimization. European Journal of Operational Research 262:682–692
- Bonnans JF, Shapiro A (2013) Perturbation Analysis of Optimization Problems. Springer Science & Business Media
- Borwein JM, Zhu QJ (2005) Variational Techniques and Multifunctions. In: Techniques of Variational Analysis. Springer, New York, NY, pp 165–241
- Chuong TD (2013) Derivatives of the Efficient Point Multifunction in Parametric Vector Optimization Problems. J Optim Theory Appl 156:247–265. doi: 10.1007/s10957-012-0099-1
- Deng X, Zhao W (2021) S-derivative of perturbed mapping and solution mapping for parametric vector equilibrium problems. Journal of Inequalities and Applications 2021:1–16
- Diening, Lars, Johannes Storn, and Tabea Tscherpel. "On the Sobolev and L^p-Stability of the L^2- Projection." SIAM Journal on Numerical Analysis 59.5 (2021): 2571-2607.
- Elsisy MA, Eid MH, Osman MSA (2017) Qualitative analysis of basic notions in parametric rough convex programming (parameters in the objective function and feasible region is a rough set). OPSEARCH 54:724– 734. doi: 10.1007/s12597-017-0300-2
- Gunantara N (2018) A review of multi-objective optimization: Methods and its applications. Cogent Engineering 5:1502242
- Julián S , Vicenç T (2016) Improving the characterization of P-stability for applications in network privacy, Discrete Applied MathematicsVolume 206, 19 June 2016, Pages 109- 114
- Kasimbeyli R, Ozturk ZK, Kasimbeyli N, Yalcin GD, Erdem BI (2019) Comparison of some scalarization methods in multiobjective optimization. Bulletin of the Malaysian Mathematical Sciences Society 42:1875– 1905
- Kjeldsen TH (2000) A contextualized historical analysis of the Kuhn–Tucker theorem in nonlinear programming: the impact of World War II. Historia mathematica 27:331–361
- Kolbin VV, Perestoronin DS (2018) Optimality and Existence of the Solution of Stochastic Multi– Objective Optimization Problem. Journal of Algebra and Applied Mathematics 17:145–156
- Kuhn HW (2014) Nonlinear programming: a historical view. In: Traces and emergence of nonlinear programming. Springer, pp 393–414
- Liang X, Wang X, Zhang X, Liu C. Lp stability analysis of neural networks with multiple time-varying delays. Journal of the Franklin Institute. 2023 Sep 1;360(13):10386-408.
- Li M, Li S, Fang Z (2012) Stability and sensitivity analysis of solutions to weak vector variational inequalities. Set-Valued and Variational Analysis 20:111–129
- Li SJ, Li MH (2011) Sensitivity analysis of parametric weak vector equilibrium problems. Journal of Mathematical Analysis and Applications 380:354–362
- Li SJ, Yan H, Chen G-Y (2003) Differential and sensitivity properties of gap functions for vector variational inequalities. Mathematical Methods of Operations Research 57:377–391
- Mordukhovich BS (2006) Variational analysis and generalized differentiation II: Applications. Springer
- Newhouse S (2004) Cone-fields, domination, and hyperbolicity. Modern dynamical systems and applications 419–432
- Osman MSA (1977) Qualitative analysis of basic notions in parametric convex programming. I. Parameters in the constraints. Aplikace matematiky 22:318–332
- Osman MSA (1977) Qualitative analysis of basic notions in parametric convex programming. II. Parameters in the objective function. Aplikace matematiky 22:333–348
- Oyelami, Benjamin Oyediran, and Sam Olatunji Ale. "Application of E^ p-stability to impulsive financial model." International Journal of Analysis and Applications 2.1 (2013): 38-53.
- Rockafellar RT (2015) Convex analysis. In: Convex analysis. Princeton university press
- Ruszczynski A (2011) Nonlinear optimization. In: Nonlinear optimization. Princeton university press
- Shi DS (1991) Contingent derivative of the perturbation map in multiobjective optimization. Journal of Optimization Theory and Applications 70:385–396
- Shokri, Ali, et al. "A new class of two-step P-stable TFPL methods for the numerical solution of secondorder IVPs with oscillating solutions." Journal of Computational and Applied Mathematics 354 (2019): 551-561.
- Tanino T (1988) Sensitivity analysis in multiobjective optimization. Journal of Optimization Theory and Applications 56:479–499
- Tanino T (1988) Stability and sensitivity analysis in convex vector optimization. SIAM Journal on Control and Optimization 26:521–536
- Tung LT (2021) On higher-order proto-differentiability and higher-order asymptotic proto-differentiability of weak perturbation maps in parametric vector optimization. Positivity 25:579–604. doi: 10.1007/s11117-020-00778-2
- Zhang, D., Moreno, J. A., & Reger, J. (2022). Homogeneous L p Stability for Homogeneous Systems. IEEE Access, 10, 81654-81683.
- Zheng XY (2020) Well-Posed Solvability of Convex Optimization Problems on a Differentiable or Continuous Closed Convex Set. SIAM Journal on Optimization 30:490–512