Results 261 to 270 of about 6,627 (303)

On duality in linear fractional functionals programming

Zeitschrift für Operations Research, 1972
The paper formulates a dual program for a given linear fractional functionals program (L.F.F.P.) and proves the duality theorem and its converse for the same. Special feature of the paper is that both the primal and the dual programs are L. F. F. Ps. and can easily be solved by the existing standard techniques.
I. C. Sharma, Kanti Swarup
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Parametric Analysis in Linear Fractional Programming

Operations Research, 1986
We consider the parametric analysis for a linear fractional programming problem with a scalar parameter in the right-hand side of the restrictions. A method we develop determines the optimal value of the objective function as well as the optimal solution of the parametric problem.
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Solving linear fractional bilevel programs

Operations Research Letters, 2004
The authors give a geometrical characterization of the optimal solution to the linear fractional bilevel programming (LFBP) problem in terms of what is called a boundary feasible extreme point. It is assumed that the second level optimal solution sets are singletons. The results extend the characterization proved by \textit{Y. H. Liu} and \textit{S. M.
Herminia I. Calvete, Carmen Galé
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A Linear Fractional Program with Homogeneous Constraints by

OPSEARCH, 1999
This paper proposes an algorithm for solving a linear fractional functionals program when some of its constraints are homogeneous. Using these homogeneous constraints a transformation matrix T is constructed. Matrix T transforms the given problem into another linear fractional functional program but with fewer constraints.
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Markov Renewal Programming by Linear Fractional Programming

SIAM Journal on Applied Mathematics, 1966
Markov renewal programming is treated by linear fractional programming. Particular attention is given to the resolution of tied policies that minimize expected cost per unit time. The multichain case is handled by a decomposition approach.
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Bicriteria linear fractional programming

Journal of Optimization Theory and Applications, 1982
As a step toward the investigation of the multicriteria linear fractional program, this paper provides a thorough analysis of the bicriteria case. It is shown that the set of efficient points is a finite union of linearly constrained sets and the efficient frontier is the image of a finite number of connected line segments of efficient points. A simple
Choo, E. U., Atkins, D. R.
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Equivalence in linear fractional programming

Optimization, 1992
In this paper two algorithms are suggested for solving a linear fractional problem whatever the feasible region is. Such algorithms can be interpreted as a modified version of Martos and Charnes-Cooper algorithms. Successively, it will be shown that the two methods are algorithmically equivalent in the sense that they generate the same finite sequence ...
A. Camibini, L. Martein
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Equivalence of various linearization algorithms for linear fractional programming

ZOR Zeitschrift f�r Operations Research Methods and Models of Operations Research, 1989
The author shows that the linearization methods proposed by \textit{J. R. Isbell} and \textit{W. H. Marlow} [Nav. Res. Logist. Quart. 3, 71-94 (1956)], \textit{O. L. Mangasarian} [J. Oper. Res. Soc. Japan 12, 1-10 (1969; Zbl 0257.90043)], \textit{G. R. Bitran} and \textit{T. L. Magnanti} [Oper. Res.
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Parametric Solution of Bicriterion Linear Fractional Programs

Operations Research, 1985
We show how certain bicriterion fractional programs can be reduced to a one parameter linear program and a series of one-dimensional maximizations. The resulting algorithm is easily implemented using the PARAROW option of MPSX, and has readily solved problems having up to 300 variables and 150 constraints.
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Comparison of duality models in fractional linear programming

Zeitschrift für Operations Research, 1977
This paper deals with the duality models in fractional linear programming presented in the last years bySwarup, Kaska, Sharma andSwarup and other authors.
Jaromir Abrham, S. Luthra
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