Query Optimization : A Metaheuristics Approach Using Modified Memetics Algorithm (MMA)

Abstract

The more complex business process of a system, the greater data that is stored. Increase of data transactions has an impact on a system performance. Therefore it is needed to optimize the query processing on data storage to maintain and improve the system performance. A memetics algorithm (MA) is a population-based metaheuristics approach which is the development of traditional genetics algorithms (GA) combined with local search (LS) technique. By using tabu search (TS) technique on the crossover operation in GA, this research proposes the modified memetics algorithm (MMA) for query optimization. The result shows that the processing time of the optimized (MMA) query is faster than the unoptimized query.