Sufficient Conditions for a Minimum of a Strongly Quasiconvex Function on a Weakly Convex Set
Matematičeskie zametki, Tome 111 (2022) no. 1, pp. 39-53.

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We consider a finite-dimensional minimization problem for a strongly quasiconvex function on a weakly convex set. We obtain sufficient conditions for its solution expressed in terms of the strong quasiconvexity constants of the objective function and the weak convexity of the admissible set of arguments, as well as their local characteristics. We separately consider the case of specifying an admissible set by the Lebesgue set of a weakly convex function. For the case of a differentiable objective function, we establish sufficient conditions for a local minimum, including a “strong” stationarity condition and indicate the radius of the corresponding neighborhood.
Keywords: strongly quasiconvex function, strongly and weakly convex sets and functions, subdifferential, normal cone, radius of the neighborhood of a local minimum.
Mots-clés : sufficient conditions for a minimum
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S. I. Dudov; M. A. Osiptsev. Sufficient Conditions for a Minimum of a Strongly Quasiconvex Function on a Weakly Convex Set. Matematičeskie zametki, Tome 111 (2022) no. 1, pp. 39-53. http://geodesic.mathdoc.fr/item/MZM_2022_111_1_a4/

[1] J. P. Vial, “Strong and weak convexity of sets and functions”, Math. Oper. Res., 8:2 (1983), 231–259 | DOI | Zbl

[2] E. S. Polovinkin, M. V. Balashov, Elementy vypuklogo i silno vypuklogo analiza, Fizmatlit, M., 2007 | Zbl

[3] G. E. Ivanov, Slabo vypuklye mnozhestva i funktsii, Fizmatlit, M., 2007

[4] Z. Y. Wu, “Sufficient global optimality conditions for weakly convex minimization problems”, J. Glob. Optim., 39 (2007), 427–440 | DOI | Zbl

[5] M. Balashov, “About the gradient projection algorithm for a strongly convex function and a proximally smooth set”, J. Convex Anal., 24:2 (2017), 493–500 | MR | Zbl

[6] M. Balashov, B. Polyak, A. Tremba, “Gradient projection and conditional gradient methods for constrained nonconvex minimization”, Numer. Funct. Anal. Optim., 41:7 (2020), 822–849 | DOI | Zbl

[7] H. Karimi, J. Nutini, M. Schmidt, “Linear convergence of gradient and proximal-gradient methods under the Polyak–Lojasiewicz condition”, Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Comput. Sci., 9851, eds. P. Frasconi, N. Landwehr, G. Manco, J. Vreeken, Springer, Cham, 2016 | DOI

[8] D. Drusvyatskiy, A. S. Lewis, “Error bounds, auadratic growth, and linear convergence of proximal methods”, Math. Oper. Res., 43:3 (2016), 919–948 | DOI

[9] D. Damek, D. Drusvyatskiy, K. J. MacPhee, C. Paquette, Subgradient Methods for Sharp Weakly Convex Functions, 2019, arXiv: 1803.02461

[10] X. Li, Z. Zhu, A. Man-Cho So, J. D Lee, Incremental Methods for Weakly Convex Optimization, 2019, arXiv: 1907.11687

[11] J. C. Duchi, F. Ruan, Stochastic Methods For Composite and Weakly Convex Optimization Problems, 2018, arXiv: 1703.08570v3

[12] S. I. Dudov, M. A. Osiptsev, “Kharakterizatsiya resheniya zadach silno-slabo vypuklogo programmirovaniya”, Matem. sb., 212:6 (2021), 43–72 | DOI | Zbl

[13] Yu. G. Reshetnyak, “Ob odnom obobschenii vypuklykh poverkhnostei”, Matem. sb., 40:3 (1956), 381–398 | MR | Zbl

[14] N. B. Efimov, S. B. Stechkin, “Opornye svoistva mnozhestv v banakhovykh prostranstvakh i chebyshevskie mnozhestva”, Dokl. AN SSSR, 127:2 (1959), 254–257 | MR | Zbl

[15] H. Federer, “Curvature measures”, Trans. Amer. Math. Soc., 93 (1959), 418–491 | DOI | Zbl

[16] F. H. Clarke, R. J. Stern, P. R. Wolenski, “Proximal Smoothness and Lower-$C^2$ Propoerty”, J. Convex Anal., 2:1-2 (1995), 117–144 | MR | Zbl

[17] R. A. Poliquin, R. T. Rockafellar, “Prox-regular functions in variational analysis”, Trans. Amer. Math. Soc., 348 (1996), 1805–1838 | DOI | Zbl

[18] R. A. Poliquin, R. T. Rockafellar, L. Thibault, “Local differentiability of distance functions”, Trans. Amer. Math. Soc., 352 (2000), 5231–5249 | DOI | Zbl

[19] F. Bernard, L. Thibault, N. Zlateva, “Characterization of prox-regular sets in super reflexive Banach spaces”, J. Convex Anal., 13 (2006), 525–559 | MR | Zbl

[20] R. Janin, Sur la dualite et la sensibilite dans les problemes de programmation mathematique, These, Universite de Paris, 1974 | Zbl

[21] R. T. Rockafellar, “Favorable classes of Lipschitz continuous functions in subgradient optimization”, Progress in Nondifferentiable Optimization, IIASA Collab. Proc. Ser., 1982, 125–144

[22] F. Bernard, L. Thibault, N. Zlateva, “Prox-regular sets and epigraphs in uniformly convex Banach spaces: Various regularities and other properties”, Trans. Amer. Math. Soc., 363 (2011), 2211–2247 | DOI | Zbl

[23] A. I. Korablev, “O relaksatsionnykh metodakh minimizatsii psevdovypuklykh funktsii”, Issled. po prikl. matem., 8, Izd-vo Kazanskogo un-ta, Kazan, 1980, 3–8 | MR | Zbl

[24] F. P. Vasilev, Metody optimizatsii, Ch. I, MTsNMO, M., 2011

[25] M. V. Iovanovich, “Zamechanie o silno vypuklykh i kvazivypuklykh funktsiyakh”, Matem. zametki, 60:5 (1996), 778–779 | DOI | MR | Zbl

[26] F. Klark, Optimizatsiya i negladkii analiz, Nauka, M., 1988 | MR | Zbl

[27] B. T. Polyak, “Teoremy suschestvovaniya i skhodimost minimiziruyuschikh posledovatelnostei dlya zadach na ekstremum pri nalichii ogranichenii”, Dokl. AN SSSR, 166:2 (1966), 287–290 | MR | Zbl

[28] V. F. Demyanov, L. V. Vasilev, Nedifferentsiruemaya optimizatsiya, Nauka, M., 1981 | MR | Zbl

[29] B. T. Polyak, Vvedenie v optimizatsiyu, Nauka, M, 1983 | Zbl