Abstract
We focus on optimality conditions for an important class of nonconvex and nonsmooth optimization problems, where the objective and constraint functions are presented as a difference of two tangentially convex functions. The main contribution of this paper is to clarify several kinds of stationary solutions and their relations, and establish local optimality conditions with a nonconvex feasible set. Finally, several examples are given to illustrate the effectiveness of the obtained results.
Similar content being viewed by others
References
Ahn M, Pang JS, Xin J (2017) Difference-of-convex learning: directional stationarity, optimality, and sparsity. SIAM J Optim 27(3):1637–1665
Astorino A, Fuduli A, Gaudioso M (2012) Margin maximization in spherical separation. Comput Optim Appl 53:301–322
Bagirov AM, Ugon J (2018) Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms. Optim Method Softw 33:194–219
Bagirov AM, Taheri S, Ugon J (2016) Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems. Pattern Recongnit 53:12–24
Bazaraa MS, Sherali HD, Shetty CM (2006) Nonlinear programming: theory and algorithms, 3rd edn. Wiley, NewYork
Beck A (2017) First-order methods in optimization. SIAM, Philadelphia
Borwein JM, Lewis AS (2010) Convex analysis and nonlinear optimization: theory and examples. Springer, New York
Cesarone F, Scozzari A, Tardella F (2020) An optimization-diversification approach to portfolio selection. J Global Optim 76:245–265
Chen PC, Hansen P, Jaumard B, Tuy H (1998) Solution of the multisource Weber and conditional Weber problems by d.c. programming. Oper Res 46:548–562
Clarke FH (1998) Nonsmooth analysis and control theory. Springer, NewYork
Clarke FH (2013) Functional analysis, calculus of variations and optimal control. Springer, NewYork
Daskalakis C, Panageas I (2018) The limit points of (optimistic) gradient descent in min-max optimization. Adv Neural Inf Process Syst 9236–9246
Delfour MC (1994) Shape analysis via oriented distance functions. J Funct Anal 123:129–201
Dutta J, Lalitha CS (2013) Optimality conditions in convex optimization revisited. Optim Lett 7:221–229
Eberle S (2008) A polynomial algorithm for a NP-hard to solve optimization problem. Dissertation, LMU München, Faculty of Physics
Hiriart-Urruty JB (1985) Generalized differentiability, duality and optimization for problems dealing with differences of convex functions. Lecture Notes in Economics and Math Systems, vol 256. Springer, Berlin, pp 37–70
Holmberg K, Tuy H (1999) A production-transportation problem with stochastic demand and concave production costs. Math Program 85:157–179
Horst R, Thoai NV (1999) DC programming: overview. J Optim Theory Appl 103:1–43
Horst R, Tuy H (1990) Global optimization. Springer, Berlin
Jara-Moroni F, Pang JS, Wächter A (2018) A study of the difference-of-convex approach for solving linear programs with complementarity constraints. Math Program 169:221–254
Joki K, Bagirov AM, Karmitsa N, Mäkelä MM, Taheri S (2018) Double bundle method for finding Clarke stationary points in nonsmooth DC programming. SIAM J Optim 28:1892–1919
Lasserre JB (2010) On representations of the the feasible set in convex optimization. Optim Lett 4:1–5
Lemaréchal M (1986) An introduction to the theory of nonsmooth optimization. Optimization 17:827–858
Le Thi HA, Pham Dinh T (2005) The DC (difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems. Ann Oper Res 133:23–46
Le Thi HA, Pham Dinh T (2018) DC programming and DCA: thirty years of developments. Math Program 169:5–68
Lobo MS, Fazel M, Boyd S (2007) Portfolio optimization with linear and fixed transaction costs. Ann Oper Res 152:341–365
Markowitz H (1952) Portfolio selection. J Financ 7:77–91
Markowitz H (1959) Portfolio selection: efficient diversification of investments. Cowles Foundation for Research in Economics at Yale University, Monograph 16. Wiley, New York
Martínez-Legaz JE (2015) Optimality conditions for pseudoconvex minimization over convex sets defined by tangentially convex constraints. Optim Lett 9:1017–1023
Martínez-Legaz JE, Volle M (1999) Duality in DC programming: the case of several DC constraints. J Math Anal Appl 237:657–671
Mashkoorzadeh F, Movahedian N, Nobakhtian S (2019) Optimality conditions for nonconvex constrained optimization problems. Numer Funct Anal Optim 40:1918–1938
Mifflin R (1977) Semismooth and semiconvex functions in constrained optimization. SIAM J Control Optim 15:959–972
Ordin B, Bagirov AM (2015) A heuristic algorithm for solving the minimum sum-of-squares clustering problems. J Global Optim 61:341–361
Pang JS, Razaviyayn M, Alvarado A (2017) Computing B-stationary points of nonsmooth DC programs. Math Oper Res 42:95–118
Penot JP (1998) On the minimization of difference functions. J Global Optim 12:373–382
Prigent JL (2007) Portfolio optimization and performance analysis. CRC Financial Mathematics Series. Chapman and Hall, Boca Raton
Pshenichnyi BN (1971) Necessary conditions for an extremum. Marcel Dekker Inc, New York
Rau-Bredow H (2003) Derivatives of value at risk and expected shortfall. Technical report, University of Würzburg
Sanjabi M, Razaviyayn M, Lee JD (2018) Solving non-convex non-concave min-max games under Polyak–Łojasiewicz condition. arXiv preprint arXiv:1812.02878
Singer I (2006) Duality for nonconvex approximation and optimization. Springer, Berlin
Studniarski M (1986) Necessary and sufficient conditions for isolated local minima of nonsmooth functions. SIAM J Control Optim 24:1044–1049
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mashkoorzadeh, F., Movahedian, N. & Nobakhtian, S. The DTC (difference of tangentially convex functions) programming: optimality conditions. TOP 30, 270–295 (2022). https://doi.org/10.1007/s11750-021-00615-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11750-021-00615-z
Keywords
- Nonconvex optimization
- Nonsmooth optimization
- Optimality conditions
- Tangential subdifferential
- Difference of tangentially convex functions