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Multiobjective programming with (p, r)-invexity

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A nonlinear multiobjective programming problem is considered where the functions involved are differentiable. In this work, we generalize some scalar optimization theory results making them applicable to vectorial optimization. By using the concept of (p, r)-invexity we give a new characterization of solutions of multiobjective programming problems. To do this, we introduce the definitions of stationary points and Kuhn-Tucker points for multiobjective programming problems. We prove, for unconstrained multiobjective programming problems with (p,r)-invex functions, that the equivalence between optimal solutions and stationary points remains true when several objective functions are optimized instead of one objective function. Moreover, we give two types of Kuhn-Tucker optimality conditions for constrained multiobjective programming problems. For this purpose, we generalize Martin's [16] definition of KT-invex problems to vectorial optimization problems with (p,r)-invex functions.
Rocznik
Strony
31--46
Opis fizyczny
Bibliogr. 23 poz.
Twórcy
autor
  • Faculty of Mathematics, University of Łódź
Bibliografia
  • [1] T. Antczak, Generalized r-convexity in mathematical programming, preprint University of Lódz, 1997.
  • [2] --, (pr),-invex sets and functions, preprint University of Lódz, 1998.
  • [3] --, On saddle points and duality for a class of (p, r)-invex problems, preprint University of Lódz, 1999.
  • [4] --, On(pr),-invexity-type nonlinear programming problems, to be published
  • [5] C. R. Bector, S. K. Sune j a, C. S. Laitha, Generalized B-vex functions and generalized B-vex programming, Journal of Optimization Theory and Applications Vol. 76, No.3, 1993, 561-576.
  • [6] A. Ben-Israel, B. Mond, What is invexity?, Journal of Australian Mathematical Society Ser.B 28, 1986,.1-9.
  • [7] B. D. Craven, Lagrangian conditions and quasiduality, Bulletin of the Australian Mathematical Society Vol. 16, 1977, 325-339.
  • [8] --, Invex functions and constrained local minima, Bulletin of the Australian Mathematical Society Vol. 24, 1981, 357-366.
  • [9] --, B. M. Glover, Invex functions and duality, Journal of Australian Mathematical Society Ser.A Vol. 39, 1985, 1-20.
  • [10] R. R. Egudo, Proper efficiency and multi-objective duality in nonlinear programming, Journal of Information and Optimization Science 8, 1987 155-166.
  • [11] M. A. Geoffrion, Proper efficiency and the theory of vector maximization, Journal of Mathematical Analysis and Applications 22, 1968, 613-630.
  • [12] M. A. Hanson, Onsufficiency of the Kuhn-Tucker conditions, Journal of Mathematical Analysis and Applications 80, 1981, 545-550.
  • [13] --, B. Mond, Necessary and sufficient conditions in constrained optimization, Mathematical Programming 37, 1987, 51-58.
  • [14] V. Jeyakumar, B. Mond, On generalised convex mathematical programming, Journal of Australian Mathematical Society Ser.B 34, 1991, 43-53.
  • [15] O. L. Mangasarian, Nonlinear programming, McGraw-Hill, New York 1969.
  • [16] D. H. Martin, The essence of invexity, Journal of Optimization Theory and Applications Vol. 42, 1985, 65-76.
  • [17] R. Osuna-Gomez, A. Beato-Moreno, A. Rufian-Lizana, Generalized convexity in multiobjective programming, Journal of Mathematical Analysis and Applications 233, 1999, 205-220.
  • [18] P. Ruiz-Canales, A. Rufian-Lizana, A characterization of weakly efficient poinis, Mathematical Programming 68, 1995, 205-212.
  • [19] P. H. Sach, B. D. Craven, Invexity in multifunction optimization, Numerical Functional Analysis and Optimization 12(3&4), 1991, 383-394.
  • [20] C. Singh, Optimality Conditions in Multiobjective Differentiable, Programming, Journal of Optimization Theory and Applications, Vol. 53, 1987, 115-123.
  • [21] T. Weir, Proper efficiency and duality for vector valued optimization problems, Journal of Australian Mathematical Society Ser.A 43, 1987, 21-34.
  • [22] --, B. Mond, Pre-invex functions in multiple objective optimization, Journal of Mathematical Analysis and Applications 136, 1988, 29-38.
  • [23] D. J. White, Vector maximisation and Lagrange multipliers, Mathematical Programming 31, 1985, 192-205.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA3-0043-0021
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