Ant Colony based Optimization Approach for Synthesis of MVL Functions

M. Abd-El-Barr (Kuwait)


MVL, multi-valued logic, synthesis, functional optimization, and ACO.


Recently, interest in multiple-valued logic (MVL) has been renewed and intensified in the hope to overcome some of the binary logic limitations. One important advantage of MVL is the increase in functionality. The search space for finding optimal MVL function synthesis is enormous. There are 324)( 24 2 == n r r 2-variable 4-valued functions. Iterative heuristics offer the possibility of exploring larger solution space in arriving at near optimal solutions. In this paper, an Ant Colony Optimization (ACO) based algorithm for synthesis of Multiple-Valued Logic (MVL) functions is proposed. The algorithm is tested using 50000 randomly generated 2-variable 4-valued functions. The results obtained using the proposed approach was compared to those obtained using existing direct cover techniques and iterative heuristics-based approaches. The results obtained show that the proposed algorithm outperforms other approaches in terms of the average number of product terms required to realize a given MVL function.

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