Though circumscription was introduced by McCarthy over a decade ago, there has been relatively 
little work on algorithms for computing circumscriptive databases. In this paper, we develop 
algorithms to compute the preferred models of circumscriptive databases at compile-time using 
mixed integer linear programming techniques. Two advantages of this (bottom-up) approach 
are that it makes efficient re-use of previous computations and it provides much faster 
run-time performance. Some other advantages of using linear programming to automate 
deduction at compile time is that its re-optimization facilities elegantly accommodate 
database updates and also that it leads to a completely declarative formulation in which 
ordering of rules and literals in rule bodies plays no real role. Finally, we plan to use a 
standard relational database system as our run-time environment; this should yield 
relatively fast run-time processing, and provide a more expressive query language in which 
aggregates and the like can be expressed easily.