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On dual problems of second order for (η, ξ)-bonvex interval-valued control problems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper studies the dual problems of second order, associated with a new class of (η, ξ)-bonvex interval-valued variational control problems. More precisely, by considering the corresponding necessary optimality conditions, we prove the associated duality (weak, strong, strictly converse) results under the new (η, ξ)- bonvexity assumptions of the involved functionals. In addition, illustrative examples are provided in order to highlight the theoretical elements established in the paper.
Rocznik
Strony
5--25
Opis fizyczny
Bibliogr. 23 poz., rys.
Twórcy
  • Department of Applied Mathematics, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
  • Department of Applied Mathematics, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
  • Academy of Romanian Scientists, 54 Splaiul Independentei, 050094 Bucharest, Romania
  • Fundamental Sciences Applied in Engineering - Research Center (SFAI), National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
autor
  • College of Science, Hohai University, Nanjing 210098, China
  • Department of Mathematics, Indian Institute of Technology Patna, Patna, India
autor
  • College of Science, Hohai University, Nanjing 210098, China
Bibliografia
  • Ahmad, I., Jayswal, A., Al-Homidan, S., and Banerjee, J. (2019) Sufficiency and duality in interval-valued variational programming. Neural Comput. Appl., 31(8) 4423–4433.
  • Al-Awami, A.T., Amleh, N.A. and Muqbel, A.M. (2017) Optimal Demand Response Bidding and Pricing Mechanism With Fuzzy Optimization: Application for a Virtual Power Plant. IEEE Trans. Ind. Appl., 53(5), 5051–5061.
  • Babazadeh, R. (2019) Application of Fuzzy Optimization to Bioenergy-Supply-Chain Planning under Epistemic Uncertainty: A New Approach. Ind. Eng. Chem. Res., 58(16) 6519–6536.
  • Bector, C.R., Chandra, S. and Husain, I. (1984) Generalized concavity and duality in continuous programming. Ufilifas Math., 25 171–190.
  • Bector, C.R. and Husain, I. (1992) Duality for multiobjective variational problems. J. Math. Anal. Appl., 166(1) 214–229.
  • Beck, A. and Ben-Tal, A. (2009) Duality in robust optimization: Primal worst equals dual best. Oper. Res. Lett., 37 1–6.
  • Dhingra, V. and Kailey, N. (2022) Optimality and duality for secondorder interval-valued variational problems. J. Appl. Math. Comput., 68 3147–3162.
  • Esmaelzadeh, R. (2014) Low-thrust orbit transfer optimization using a combined method. Int. J. Comput.Appl., 89(4) 20–24.
  • Guo,Y., Ye, G., Liu, W., Zhao, D. and Treanţă, S. (2021) Optimality conditions and duality for a class of generalized convex interval-valued optimization problems. Mathematics, 9 2979.
  • Guo,Y., Ye, G., Liu, W., Zhao, D. and Treanţă, S. (2022) On symmetric gH-derivative applications to dual interval-valued optimization problems. Chaos, Solitons and Fractals, 158 112068.
  • Guo,Y., Ye, G., Liu, W., Zhao, D. and Treanţă, S. (2023) Solving nonsmooth interval optimization problems based on interval-valued symmetric invexity. Chaos, Solitons and Fractals, 174 113834.
  • Ishibuch, H. and Tanaka, H. (1990) Multiobjective programming in optimization of the interval objective function. Eur. J. Oper. Res., 48(2) 219–225.
  • Jeyakumar, V., Li, G. and Lee, G.M. (2012) Robust duality for generalized convex programming problems under data uncertainty. Nonlin. Anal. Theory Meth. Appl., 75 1362–1373.
  • Koopialipoor, M. and Noorbakhsh, A. (2020) Applications of artificial intelligence techniques in optimizing drilling. In: Emerging Trends in Mechatronics, Intechopen, London 89–118.
  • Moore, R.E. (1979) Methods and Applications of Interval Analysis. Society for Industrial and Applied Mathematics, Philadelphia.
  • Mond, B. and Hanson, M.A. (1968) Duality for control problems. SIAM J. Control, 6 114–120.
  • Treanţă, S. (2021a) On a dual pair of multiobjective interval-valued variational control problems. Mathematics, 9 893.
  • Treanţă, S. (2021b) Efficiency in uncertain variational control problems. Neural Comput. Appl., 33(11) 5719–5732.
  • Treanţă, S. (2021c) On a class of constrained interval-valued optimization problems governed by mechanical work cost functionals. J. Optim. Theory Appl., 188(3) 913–924.
  • Treanţă, S. (2022a) Characterization results of solutions in interval-valued optimization problems with mixed constraints. J. Global Optim., 82 951–964.
  • Treanţă, S. (2022b) LU-optimality conditions in optimization problems with mechanical work objective functionals. IEEE Trans. Neur. Net. Lear., 33(9) 4971–4978.
  • Upadhyay, B.B., Ghosh, A., Mishra, P. and Treanţă, S. (2022) Optimality conditions and duality for multiobjective semi-infinite programming problems on Hadamard manifolds using generalized geodesic convexity. RAIRO Oper. Res., 56(8) 2037–2065.
  • Upadhyay, B.B., Ghosh, A. and Treanţă, S. (2023) Optimality conditions and duality for nonsmooth multiobjective semi-infinite programming problems on Hadamard manifolds. Bull. Iran. Math. Soc., 49 45.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-78be0114-2be7-47fa-80dd-2e378c38bdbe
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