Management of Software Projects with GAs

A Project Scheduling Problem consists in deciding “who does what” during the software project lifetime. This is a capital application in the practice of software engineering, since the total budget and human resources involved must be managed optimally to end in a successful project. In short, the main interest of a company is to reduce the time and the cost of the project, and these two goals are in conflict. The problem addressed in this article accounts for times, human skills, budget, and global complexity. This makes our study very realistic and similar to an actual software project planning scenario [3]. In this work we tackle the problem by using genetic algorithms to solve 36 different software project scenarios. Thanks to our newly developed instance generator we can perform structured studies about the influence in the solutions of the most important attributes of the problem. Our conclusions show that GAs are quite flexible and accurate techniques for this application, and can be an important tool for project managers [1]. Metaheuristics and, in particular, GAs are not as intensively applied in the software engineering domain as they are in fields like engineering, mathematics, economy, telecommunications, or bioinformatics [2]. However, the work of Clarke et al. [4] is a good reference for solving software engineering problems with metaheuristics.