Comparison of Parallel Distributed Metaheuristic Optimization Algorithms in Computing Reducts

Optimization algorithms have been applied in many fields. This paper presents performance of Genetics Algorithm and Runner-Roots Algorithm in computation of Reducts. An important area of research in Data Mining is knowledge discovery. Massive amounts of data exists in the health industry and problem is to sift through it, removing redundancy and at the same time retaining enough information to base decisions upon. As the amounts of data is huge, it is required use parallel distributed optimization methods for efficient search and PC Clusters for fast computations. The results indicate the huge benefits of parallel distributed systems to be utilized in such applications.