Dinkelbach's algorithm
ID: dinkelbach-s-algorithm
To maximize on a nonempty compact feasible set , assume are continuous and . Define the parametric optimal valueIf , then for , , and for . This follows by comparing each ratio with and multiplying by its positive denominator.
Starting with a feasible ratio , choose a global maximizer of and updateThe values increase while staying below . Their limit must be : otherwise continuity of and an upper bound on would force increments bounded away from zero. A zero residual is an exact certificate. These assumptions give attained subproblems and convergence; a merely local inner optimizer does not provide this certificate. The method replaces a ratio objective by a succession of difference objectives. [ref]
On Nonlinear Fractional Programming by Werner Dinkelbach. Werner Dinkelbach, On Nonlinear Fractional Programming, Management Science13(7),1967, pp492–498; publisher abstract describes the ratio/parametric relationship
New to topics? Read the docs here!