Fractional Programming |
Contents
Preface page | 3 |
Linear fractional programming | 20 |
Nonlinear fractional programming | 35 |
Copyright | |
10 other sections not shown
Common terms and phrases
affine function algorithm applications assumed B. D. Craven chapter component computed concave function concave-convex fractional program Consider constant convergence convex function convex set Den+ denominator denotes differentiable function Dinkelbach dual problem dual program eigenvalue equivalent program example feasible for LP feasible point feasible set follows function f given gradient Hence inequalities invex iteration Karush-Kuhn-Tucker conditions Lagrange multiplier Lagrangian dual Lemma Let let f LFex linear constraints linear fractional program linesearch local maximum Mathematical Programming matrix Maximize f(x Maximize N(x)/D(x Minimize minimum Naval Research Logistics NLF3 nonlinear fractional programs Nonlinear Programming objective function Operations Research optimum parameter positive semidefinite program LF Proof Let properties pseudoconcave pseudoconvex quadratic program quasiconvex quasimax quasimin ratio reaches a maximum replaced Research Logistics Quarterly satisfies simplex algorithm Stancu-Minasian strong dual subject to g(x Theorem TNLF TNLF+ TNLF2 unconstrained variables vector weak duality X₁ zero duality gap