Variable Ordering Algorithms Using Problem Classifying

Genetic Algorithms for the Variable Ordering Problem of Binary Decision Diagrams

Ordered binary decision diagrams (BDDs) yield a data structure for switching functions that has been proven to be very useful in many areas of computer science. The major problem with BDD-based calculations is the variable ordering problem which addresses the question of finding an ordering of the input variables which minimizes the size of the BDD-representation. In this paper, we discuss the ...

Two Strategies Based on Meta-Heuristic Algorithms for Parallel Row Ordering Problem (PROP)

Proper arrangement of facility layout is a key issue in management that influences efficiency and the profitability of the manufacturing systems. Parallel Row Ordering Problem (PROP) is a special case of facility layout problem and consists of looking for the best location of n facilities while similar facilities (facilities which has some characteristics in common) should be arranged in a row ...

Variable Ordering of BDDs with Parallel Geneti Algorithms

Comparison of variable ordering heuristics / algorithms for binary decision diagrams

Fault tree analysis is a commonly used technique to assess the systems reliability performance in terms of its components reliability characteristics. More recently, the Binary Decision Diagram (BDD) methodology has been introduced which significantly aids the analysis of the fault tree diagram. The approach has been shown to improve both the efficiency of determining the minimal cut sets of th...

A Variable Neighborhood Search for Solving the Linear Ordering Problem

A Systematic change of Neighborhood within a possibly randomized local search algorithm yields a simple and effective metaheuristic for combinatorial and global optimization. In this paper we present a Variable Neighborhood Search implementation designed to find high quality solutions for the NP-hard Linear Ordering Problem, which has a significant number of application in practice, such triang...