Multi-objective Multi-Join Query Optimization using Modified Grey Wolf Optimization

Nowadays information retrieved by a query is based upon extracting data across the world, which are located in different data sites. In distributed database management systems (DDBMS), due to partitioning or replication of data among several sites the relations required for an answer of a query may be stored at several data sites (DS). Many experimental results have showed that combination of optimal join order (OJO) and optimal selection of relations in query plan (QP) gives out better results compare to the several existing query optimising methodologies like teacher-learner based optimisation (TLBO), genetic algorithm (GA), etc. In this paper an approach has been proposed to compute a best optimal QP that could answer the user query with minimal cost values and minimum time using modified grey wolf optimisation algorithm (MGWO) which is multi-objective constrained. Proposed approach also aims for producing OJO in order to reduce the dimensionality complexity of the QP.