Volume 29 | Number 1 | Year 2016 | Article Id. IJMTT-V29P507 | DOI : https://doi.org/10.14445/22315373/IJMTT-V29P507
Dorn introduced symmetric duality in nonlinear programming by defining a program and it’s dual to be symmetric if the dual of the dual is the original problem. In the past, the symmetric duality has been studied extensively in the literature by Dantzig and Mond and Weir. Recently, Weit and Mond studied symmetric duality in the context of multi-objective programming by introducing a multi-objective analogue of the primal-dual pair presented in Mond. Although the multi-objective primal dual pair constructed in subsumes the single objective symmetric duality as a special case, the construction of seems to be somewhat restricted because the same parameter Rp (vector multiplier corresponding to various objectives) is present in both primal and dual. Further, the proof of the main duality result assumes this to be fixed in the dual problem. The main aim of this paper is to present a pair of multi-objective programming problem (P) and Duality (D) with as variable in both programs and to establish symmetric duality by associating a vector-valued infinite game to this pair. Although this construction seems to be more natural than that of [13] as it does not require to be fixed in the dual problem, it lacks the weak duality theorem as illustrated in Section3. However the case of single objective symmetric duality [7] is fully subsumed here as well, because (P) and (D) then reduce to primal – dual pair of Dantzig.
1. H.W. Corley, “Games with vector pay-offs”, Journal of Optimization theory and applications 47 (1985) 491- 498.
2. R.W. Cottle, “An infinite game with a convex-concave pay-off kernel”, Research Report No. ORC 63-19 (RN- 2), Operation Research Centre, University of California, Berkley, 1963 Unpublished.
3. B.D. Craven, “Lagrangian conditions and quasiduality”, Bull. Aust. Math. Soc. 16(1977) 325-339.
4. B.D. Craven, “Lagrangian conditions, vector minimization and local duality”, Research Report No. 37, Department of Mathematics, University of Melbourne, Australia, 1980.
5. G.B. Dantzig, E. Eisenberg and R.W. Cottle, “symmetric dual nonlinear program”, Pacific J. Math. 15(1965), 809-812.
6. W. S. Dorn, “A symmetric dual theorem for quadratic programs”, Journal of Operations Research Society of Japan 2(1960) 93-97.
7. B. Mond, “A symmetric dual theorem for nonlinear programs”, Quart of Appl. Of Math. 23(1965) 265-269.
8. B. Mond. “A symmetric duality for nonlinear programming”, OPSEARCH 13(1976) 1-10.
9. B. Mond and T. Weir, “Generalized concavity and duality”, in Generalized Concavity Optimization and Economics (eds. S.Schaible and W.T. Zeimbai), Academic Press, 1981), 263-279.
10. W. Rodder, “A generalized saddle point theory: its application to duality theory for linear vector optimum problems”, European Journal of Operation Research (1977), 55-59.
11. C. Singh, “Optimality conditions in multi objective differentiable programming”, Journal of Optimization Theory and Application 53(1987) 115-123.
12. T. Tanino, Y. Sawargi and A. Nakayama, “Theory of Multi objective Optimization (Academic Press. Inc. USA, 1985.) 13. T. Weirand B. Mond, “Symmetric and self duality in multi objective programming”, Asia- Pacific Journal of Operational Research 5(2) (1988) 124-133.
14. Gayatri Devi, Rashmita Mohanty “Non-Differentiable Fractional Programming Under Generalized d,ƞ ,ῤ ,ɵ , - Type 1 Univex Function”, International Journal of Mathematics Trends and Technology (IJMTT), vol. 21 (2014) : 2231-5373.
15. P. Rajarajeswari, A. Sahaya Sudha, “Solving a Fully Fuzzy Linear Programming Problem”, International Journal of Mathematics Trends and Technology (IJMTT), vol. 9(2014) : 2231-5373.
Dr. Riddhi Garg, "Symmetric Duality in Multi – Objective Programming," International Journal of Mathematics Trends and Technology (IJMTT), vol. 29, no. 1, pp. 39-44, 2016. Crossref, https://doi.org/10.14445/22315373/IJMTT-V29P507