An exact minimax penalty function approach to solve multitime variational problems
RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 3, pp. 637-652.

This paper aims to examine an appropriateness of the exact minimax penalty function method applied to solve the partial differential inequation (PDI) and partial differential equation (PDE) constrained multitime variational problems. The criteria for equivalence between the optimal solutions of a multitime variational problem with PDI and PDE constraints and its associated unconstrained penalized multitime variational problem is studied in this work. We also present some examples to validate the results derived in the paper.

DOI : 10.1051/ro/2019019
Classification : 26B25, 65K10, 90C30
Mots-clés : Convexity, exact minimax penalty function method, multitime variational problem, PDI, PDE constraints
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     title = {An exact minimax penalty function approach to solve multitime variational problems},
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     pages = {637--652},
     publisher = {EDP-Sciences},
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Jayswal, Anurag; Preeti. An exact minimax penalty function approach to solve multitime variational problems. RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 3, pp. 637-652. doi : 10.1051/ro/2019019. http://www.numdam.org/articles/10.1051/ro/2019019/

T. Antczak, Saddle point criteria and the exact minimax penalty function method in nonconvex programming. Taiwanese J. Math. 17 (2013) 559–581. | DOI | MR | Zbl

T. Antczak, Exactness of penalization for exact minimax penalty function method in nonconvex programming. Appl. Math. Mech. (English Ed.) 36 (2015) 541–556. | DOI | MR

T. Antczak, Exactness property of the exact absolute value penalty function method for solving convex nondifferentiable interval-valued optimization problems. J. Optim. Theory Appl. 176 (2018) 205–224. | DOI | MR | Zbl

T. Antczak, Exactness of the absolute value penalty function method for nonsmooth ( ϕ , ρ ) -invex optimization problems. Int. Trans. Oper. Res. 26 (2019) 1504–1526. | DOI | MR | Zbl

M.F.P. Costa, A.M.A.C. Rocha, R.B. Francisco and E.M.G.P. Fernandes, Firefly penalty-based algorithm for bound constrained mixed-integer nonlinear programming. Optimization 65 (2016) 1085–1104. | DOI | MR | Zbl

V.F. Demyanov and G.S. Tamasyan, Exact penalty functions in isoperimetric problems. Optimization 60 (2011) 153–177. | DOI | MR | Zbl

G. Di Pillo, S. Lucidi and F. Rinaldi, An approach to constrained global optimization based on exact penalty functions. J. Global Optim. 54 (2012) 251–260. | DOI | MR | Zbl

M.V. Dolgopolik, A unifying theory of exactness of linear penalty functions. Optimization 65 (2016) 1167–1202. | DOI | MR | Zbl

S.A. Gustafson, Investigting semi-infinite programs using penalty functions and lagrangian methods. J. Aust. Math. Soc. Ser. B 28 (1986) 158–169. | DOI | MR | Zbl

M.A. Hanson, Bounds for functionally convex optimal control problems. J. Math. Anal. Appl. 8 (1964) 84–89. | DOI | MR | Zbl

A. Jayswal and S. Choudhury, An exact l 1 exponential penalty function method for multiobjective optimization problems with exponential-type invexity. J. Oper. Res. Soc. China 2 (2014) 75–91. | DOI | MR | Zbl

A. Jayswal and S. Choudhury, An exact minimax penalty function method and saddle point criteria for nonsmooth convex vector optimization problems. J. Optim. Theory Appl. 169 (2016) 179–199. | DOI | MR | Zbl

S. Liu and E. Feng, The exponential penalty function method for multiobjective programming problems. Optim. Methods Softw. 25 (2010) 667–675. | DOI | MR | Zbl

S. Lucidi and F. Rinaldi, Exact penalty functions for nonlinear integer programming problems. J. Optim. Theory Appl. 145 (2010) 479–488. | DOI | MR | Zbl

B. Mond and M.A. Hanson, Duality for variational problems. J. Math. Anal. Appl. 18 (1967) 355–364. | DOI | MR | Zbl

A. Pitea and T. Antczak, Proper efficiency and duality for a new class of nonconvex multitime multiobjective variational problems. J. Inequal. Appl. 2014 (2014) Art. No. 333. | DOI | MR | Zbl

A. Pitea and M. Postolache, Duality theorems for a new class of multitime multiobjective variational problems. J. Global Optim. 54 (2012) 47–58. | DOI | MR | Zbl

A. Pitea, C. Udrişte and Ş. Mititelu, PDI& PDE-constrained optimization problems with curvilinear functional quotients as objective vectors. Balkan J. Geom. Appl. 14 (2009) 75–88. | MR | Zbl

A. Pitea, C. Udrişte and Ş. Mititelu, New type dualities in PDI and PDE constrained optimization problems. J. Adv. Math. Stud. 2 (2009) 81–90. | MR | Zbl

C. Udrişte and I. Ţevy, Multi-time Euler-Lagrange-Hamilton theory. WSEAS Trans. Math. 6 (2007) 701–709. | MR | Zbl

C. Udrişte, O. Dogaru and I. Ţevy, Null Lagrangian forms and Euler-Lagrange PDEs. J. Adv. Math. Stud. 1 (2008) 143–156. | MR | Zbl

C. Udrişte, P. Popescu and M. Popescu, Generalized multi-time Lagrangians and Hamiltonians. WSEAS Trans. Math. 7 (2008) 66–72. | MR

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