Interpolating greedy and reluctant algorithms

Interpolating greedy and reluctant algorithms

In a standard NP-complete optimization problem we introduce an interpolating algorithm between the quick decrease along the gradient (greedy dynamics) and a slow decrease close to the level curves (reluctant dynamics). We find that for a fixed elapsed computer time the best performance of the optimization is reached at a special value of the interpolation parameter, considerably improving the r...

Finding Minima in Complex Landscapes: Annealed, Greedy and Reluctant Algorithms

We consider optimization problems for complex systems in which the cost function has a multivalleyed landscape. We introduce a new class of dynamical algorithms which, using a suitable annealing procedure coupled with a balanced greedy-reluctant strategy drive the systems towards the deepest minimum of the cost function. Results are presented for the Sherrington-Kirkpatrick model of spin-glasses.

Parallelism and Greedy Algorithms

A number of greedy algorithms are examined <and are shown to be probably inherently sequential. Greedy algorithms are presented for finding a maximal path, for finding a . maximal set of disjoint paths in a layered dag, and for finding the largest induced subgraph of a graph that has all vertices of degree at least Ic. It is shown that for all of these algorithms, the problem of determining if ...

Greedy Algorithms

Fast interpolating algorithms in cryptography

We present two fast polynomial interpolating algorithms with knots generated in a field K by the recurrent formula of the form ( ) 1 0 1,2,.., 1; i i x x i n x α β γ − = + = − = . The running time of them is ( ) ( ) C n O n + base operations from K, where ( ) ( ) 2 log C n O n n = denotes the time needed to compute the wrapped convolution in K. Moreover, we give an application of these algorith...