An Efficient Heuristic for Linear Decomposition of Index Generation Functions

Abstract

This paper proposes a heuristic for linear decomposition of index generation functions using a balanced decision tree. The proposed heuristic finds a good linear decomposition of an index generation function by recursively dividing aset of its function values into two balanced subsets. Since the proposed heuristic is fast and requires a small amount of memory, it is applicable even to large index generation functions that cannot be solved in a reasonable time by existing heuristics. This paper shows time and space complexities of the proposed heuristic, and experimental results using some large examples to show its efficiency.