Software project scheduling by evolutionary techniques

Abstract

Due to the fast growth in software engineering nowadays most of the software companies are overlaying a highly spirited market The efficient project plans are achieved by the companies in terms of reducing the cost of constructing the software However the most complex and challenging tasks due to large scale projects are project planning and scheduling In a software project planning the project manager should have estimated the project workload and cost for scheduling the project and allocating the required resources In this research certain heuristic computation mechanisms are proposed for achieving an efficient project scheduling and resource allocation In the first phase of the research a novel approach is introduced to overcome the software project planning and scheduling problems due to previous methods In the proposed approach an event based scheduler and Ant Colony Optimization ACO algorithm are introduced for improving the flexibility and efficiency of the project scheduling and resource allocation This approach considers the different attributes such as proficiency salary and working experience of employees in order to construct the task list and employee allocation matrix Based on the constructed task list and employee allocation matrix the software development managers schedule the projects to each employee Moreover a decision tool is designed for managers to deal with the uncertainties that they face during the project scheduling Thus the effectiveness of the proposed approach is increased newline