Hybridization of Neighbourhood Search Metaheuristic with Data Mining Technique to Solve p-median Problem

Combinatorial optimizat ion is the most panoptic area in current research paper. The p-median problem which is a combinatorial optimization problem is NP-Hard in nature that realizes facilitators which serves the maximum locations. The p-median problem will be pract ical in several applicat ions areas such as escalating marketing strategies in the sphere of Management Sciences and in locating server positions in computer networks. In the proposed work the Metaheuristic based on Neighbourhood Search (NS) is hybridized with Data Min ing Technique (HDMNS) with Frequent Mining to provide a solution to p-median problem. The resulting local optimal solution from NS method serves as a basis for identification of feasible solution space that holds different possible solutions of similar size and by the application of frequent mining technique on it results in identificat ion of frequent items. Basing on the support count, most feasible solution is identified.