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A genetic algorithm for RKRO minimization
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DOI：10.1016/S0957-4174(96)00087-5.png)
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We show that there is a close relation between Ordered Kronecker Functional Decision Diagrams (OKFDDs) and two-level AND/EXOR expressions. This relation, together with efficient OKFDD algorithms, can be utilized for exact and heuristic minimization of these AND/EXOR expressions, called Reduced Kronecker Expressions (RKROs). RKROs depend on the Variable Ordering (VO) and Decomposition Type List (DTL) of the corresponding OKFDD. We propose several (exact and heuristical) minimization algorithms for fixed VO and perform experimental results. A Genetic Algorithm (GA) is applied to minimize RKROs with respect to VO and DTL in parallel. We applied our GA to a large set of benchmark functions to show the efficiency of our approach. Copyright (C) 1997 Elsevier Science Ltd
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