Heuristics for trie index minimization

Heuristics for ⊕-OBDD Minimization

Descent heuristics for unconstrained minimization

Semidefinite relaxations often provide excellent starting points for nonconvex problems with multiple local minimizers. This work aims to find a local minimizer within a certain neighborhood of the starting point and with a small objective value. Several approaches are motivated and compared with each other.

Learning Heuristics for Obdd Minimization by Evolutionary Algorithms Learning Heuristics for Obdd Minimization by Evolutionary Algorithms

Ordered Binary Decision Diagrams (OBDDs) are the state-of-the-art data structure in CAD for ICs. OBDDs are very sensitive to the chosen variable ordering, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OBDD minimization starting from a given set of basic operations. The diierence to other previous approa...

Heuristics for the Whitehead Minimization Problem

In this paper we discuss several heuristic strategies which allow one to solve the Whitehead’s minimization problem much faster (on most inputs) than the classical Whitehead algorithm. The mere fact that these strategies work in practice leads to several interesting mathematical conjectures. In particular, we conjecture that the length of most non-minimal elements in a free group can be reduced...

Evaluating iterative improvement heuristics for bigraph crossing minimization

The bigraph crossing problem, embedding the two node sets of a bipartite graph G = (V0; V1; E) along two parallel lines so that edge crossings are minimized, has application to placement optimization for standard cells and other technologies. Iterative improvement heuristics involve repeated application of some transformation on an existing feasible solution to obtain better feasible solutions....