| Summary: | Various methods have been presented for efficiently evaluating deductive databases and
logic programs. It has been shown that mixed integer programming methods can ef
fectively support minimal model, stable model and well-founded model semantics for
ground deductive databases. However, the “groundness” requirement is a huge draw
back because the ground version of a logic program can be very large when compared
to the original logic program. A novel approach, called partial instantiation, has been
developed recently which, when integrated with mixed integer programming methods,
can handle non-ground logic programs. The goal of this thesis is to explore how this
integrated framework based on partial instantiation can be optimized. In particular, we
have developed an incremental algorithm that minimizes repetitive computations for re
ducing the size of a program. We have also developed several optimization techniques
to further enhance the efficiency of our incremental algorithm, to further reduce the size
of a logic program, and to avoid redundant node expansion in partial instantiation tree.
Experimental results have shown that our algorithm and optimization techniques can
bring about significant improvement in run-time performance. Last but not least, we
have implemented the integrated framework of partial instantiation under UNIX envi
ronment.
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