Software organizations are putting efforts to improve the accuracy of the project cost estimation. This in turn helps them to allocate resources. Software cost estimation has been an area of key interest in software engineering community. Many estimation models divided among various categories have been proposed over a period of time. Function Point (FP) is one of the useful software cost estimation methodology that was first proposed twenty-five years ago using the project repository that contained information about various aspects of software project. In the last twenty five years software development productivity has grown rapidly but the complexity weight metrics values assigned to count standard FP still remain same. This fact raises critical questions about the validity of the complexity weight values and accuracy of the estimation process. The objective of this work is to present a genetic algorithm based approach to calibrate the complexity weight metrics of FP using the project repository of International Software Benchmarking Standards Group (ISBSG) dataset. The contribution of this work shows that information reuse and integration of past project's function-point structural elements improves the accuracy of software estimation process.