Genetic Algorithm and Variable neighbourhood search for BDD Variable Ordering Problem
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Abstract
The Binary Decision Diagram (BDD) is used to represent in symbolic manner a set of states. It is largely used in the field of formal checking. The variable ordering is a very important step in the BDD optimization process. A good order of variables will reduce considerably the size of a BDD. Unfortunately, the search for the best variables ordering has been showed NP-difficult. In this article, we propose a new iterative approach based on a hybrid Genetic Algorithm and Variable Neighborhood Search Algorithm. The obtained results are very encouraging and show the feasibility and effectiveness of the proposed hybrid approach.
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How to Cite
Layeb, A., Tabib, N., & Brirem, B. (2011). Genetic Algorithm and Variable neighbourhood search for BDD Variable Ordering Problem. INFOCOMP Journal of Computer Science, 10(1), 29–35. Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/324
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