A neighborhood decoupling algorithm for truncated sum minimization
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There has been considerable interest in heuristic method for minimizing multiple-valued logic functions because exact methods are intractable. This paper describes a new heuristic, called the neighborhood decoupling (ND) algorithm. It first selects a minterm and then selects an implicant, a two step process employed in previous heuristics, e.g., Besslich  and Dueck and Miller . The approach taken here more closely resembles the Dueck and Miller heuristic; however, it makes more efficient use of minterms truncated to the highest logic value. The ND-algorithm was developed in conjunction with HAMLET , a computer software created at the Naval Postgraduate School for the purpose of designing heuristics for multiple-valued logic minimization. In this paper, we present the algorithm, discuss the implementation, show that it performs consistently better than others and explain the reason for its improved performance.
The article of record as published may be found at http://dx.doi.org/10.1109/ISMVL.1990.122611Published in: Proceedings of the Twentieth International Symposium on Multiple-Valued Logic
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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