A nobel approach for effective selection of data using GA approach

The goal of query optimization is to produce optimized execution plan which minimizes execution cost. But in order to achieve this goal query optimizer must deal with NP-Complete problem. The problem is formalized as a constraint problem. In this paper we present how genetic algorithms (GA) could be applied to a group of people working in an organization for selecting a team of members who showed remarkable performances. For this purpose we defined fitness function to check the optimality of the members and how the optimality changes with the change in gene composition of a chromosome. The proposed method takes into account several important factors that affect behavior of members which contributes towards an organization: Designation, No. of working hours, Extra working hours devoted to company (Over time), Appreciation Awards, Participation in various cultural events, and their Work Experiences etc. Starting from a random initial population, the normal GA operations (selection, reproduction and mutation) to get the next population set and the process is iterated till an optimal team is produced or a fixed number of times. The proposed system is made very generic and it can be applied to any kind of organization or system by just modifying the fitness function.