Optimization of Production Systems Using Genetic Algorithms

This paper presents a Genetic Algorithm for Production Systems Optimization (GAPSO). The GAPSO finds an ordering of Condition Elements (CEs) in the rules of a Production System (PS) that results in a (near) optimal PS with respect to execution time. Finding such an ordering can be difficult since there is often a large number of ways to order CEs in the rules of a PS. Additionally, existing heuristics to order CEs in many cases conflict with each other. The GAPSO is applicable to PSs in general and no assumptions are made about the matching algorithm or the interpreter that executes the PS. The results of applying the GAPSO to some example PSs are presented. In all examples, the GAPSO found an optimal ordering of CEs in a small number of iterations.