BDD-based heuristics for binary optimization

BDD-based heuristics for binary optimization

In this paper we introduce a new method for generating heuristic solutions to binary optimization problems. We develop a technique based on binary decision diagrams. We use these structures to provide an underapproximation to the set of feasible solutions. We show that the proposed algorithm delivers comparable solutions to a state-of-the-art general-purpose optimization solver on randomly gene...

BDD Ordering Heuristics for Classical Planning

Symbolic search using binary decision diagrams (BDDs) can often save large amounts of memory due to its concise representation of state sets. A decisive factor for this method’s success is the chosen variable ordering. Generally speaking, it is plausible that dependent variables should be brought close together in order to reduce BDD sizes. In planning, variable dependencies are typically captu...

Bdd-based Logic Optimization System

BDS : A BDD - Based Logic Optimization System

This paper describes a novel logic decomposition theory and a practical logic synthesis system, BDS. It is based on a new binary decision diagrams (BDD) decomposition technique which supports all types of decomposition structures, including AND, OR, XOR, and complex MUX, both algebraic and Boolean. As a result, the method is very efficient in synthesizing both AND/OR and XOR-intensive functions...

Optimization-based heuristics for maximal constraint satisfaction

We present a new heuristic approach for maximal constraint satisfaction of overconstrained problems (MAX-CSP). This approach is based on a formulation of CSP as an optimization problem presented in a previous paper [Meseguer and Larrosa, 95], which has given good results on some classes of solvable CSP. For MAX-CSP, we have developed two heuristics for dynamic variable and value ordering, calle...