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A logarithmic barrier function method for solving nonlinear multiobjective programming problems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An interior point method for solving nonlinear multiobjective programming problems, over a convex set contained in the real space R^n, has been developed in this paper. In this method a new strictly concave logarithmic barrier function has been suggested in order to transform the orginal problem into a sequence of unconstrained subproblems. These subproblems can be solved using Newton method for determining Newton's directions along which line searches are performed. It also has been proved that the number of iterations required by the suggested algorithm to converge to an [epsilon]-optimal solution is 0(m|ln[epsilon]|), depending on predetermined error tolerance [epsilon] and the number of constraints m.
Rocznik
Strony
487--504
Opis fizyczny
Bibliogr. 12 poz.
Twórcy
autor
  • Scientific Services Department, Atomic Energy Commission P.O. Box 6091, Damascus, Syria
  • Scientific Services Department, Atomic Energy Commission P.O. Box 6091, Damascus, Syria
Bibliografia
  • De Ghellinck, G. and Vial, J. Ph. (1986) A polynomial Newton method for linear programming. Algorithmica 1, 425–453.
  • De Ghellinck, G. and Vial, J. Ph. (1987) An extention of Karmarkar’s algorithm for solving a system of linear homogenous equations on the simplex. Mathematical Programming 39, 79–92.
  • Dyer, J. (1973) A time-sharing computer program for the solution of the multiple criteria problem. Management Science 19 (12), 1379-1383.
  • Hertog, D., Roos, C. and Terlaky, T. (1992) A large-step analytic center method for a class of smooth convex programming problems. SIAM J. Optimization 2 (1), 55-70.
  • Hertog, D., Roos, C. and Terlaky, T. (1991) A potential-reduction variant of Renegar’s short- following method for linear programming. Linear Algebra and its Applications 152, 43-68.
  • Iri, M. and Imai, H. (1986) A multiplicative barrier function method for linear programming. Algorithmica 1, 455-482.
  • Karmarkar, N. (1984) A new polynomial time algorithm for linear programming. Combinatorica 4, 373-395.
  • Mehrotra, S. and Sun, J. (1990) An algorithm for convex quadratic programming that requires O( n3.5L) arithmetic operations. Mathematics of Operations Research 15 (2), 342-363.
  • Minoux, M. (1983) Programmation mathematique. Theorie et algorithmes. Dunod, Paris.
  • Renegar, J. (1988) A polynomial-time algorithm based on Newton’s method for linear Programming. Mathematical Programming 40, 59-93.
  • Steuer, R. (1986) Multiple Criteria Optimization: Theory, Computation, and Application. Wiley series in probability and mathematical statistics applied, John Wiley & Sons.
  • Wallenius, J. (1975) Comparative evaluation of some interactive approaches to multicriterion optimization. Management Science 21 (12), 1387-1396.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0007-0100
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