Title
Evolutionary-Reduced Ordered Binary Decision Diagram
Abstract
Reduced ordered binary decision diagram (ROBDD) is a memory-efficient data structure which is used in many applications such as synthesis, digital system, verification, testing and VLSI-CAD. The size of an ROBDD for a function can be increased exponentially by the number of independent variables of the function that is called “memory explosion problem”. The choice of the variable ordering largely influences the size of the OBDD especially for large input variables. Finding the optimal variable ordering is an NP-complete problem, hence, in this paper, two evolutionary methods (GA and PSO) are used to find optimal order of input variable in binary decision diagram. Some benchmarks form LGSynth91 are used to evaluate our suggestion methods. Obtained results show that evolutionary methods have the ability to find optimal order of input variable and reduce the size of ROBDD considerably.
Year
DOI
Venue
2009
10.1109/AMS.2009.130
Asia International Conference on Modelling and Simulation
Keywords
Field
DocType
memory explosion problem,evolutionary-reduced ordered binary decision,binary decision diagram,independent variable,input variable,optimal variable,evolutionary method,optimal order,np-complete problem,obtained result,large input variable,computational complexity,boolean functions,application software,boolean function,particle swarm optimization,np complete problem,gallium,data structures,genetic algorithms,computer simulation,data engineering,data structure,genetic algorithm,computational modeling
Boolean function,Particle swarm optimization,Data structure,Binary decision diagram,Theoretical computer science,Variables,Genetic algorithm,Mathematics,Exponential growth,Computational complexity theory
Conference
Citations 
PageRank 
References 
2
0.38
11
Authors
6
Name
Order
Citations
PageRank
Hossein Moeinzadeh1234.07
Mehdi Mohammadi2109150.02
Hossein Pazhoumand-dar3273.14
Arman Mehrbakhsh451.10
Navid Kheibar520.38
Nasser Mozayani69818.48