Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/3840
Title: Intelligent software project scheduling and team staffing with genetic algorithms
Authors: Stylianou, Constantinos
Andreou, Andreas S. 
Keywords: Genetic algorithm approach
Intelligent software
Management decisions
Optimisations
Project scheduling
Research efforts
Risk of failure
Software development projects
Software project
Software project management
Team staffing
Artificial intelligence
Enterprise resource management
Genetic algorithms
Personnel
Personnel selection
Personnel selection
Project management
Scheduling algorithms
Software design
Issue Date: 2011
Publisher: Springer Berlin Heidelberg
Source: 12th INNS EANN-SIG International Conference, Corfu, Greece, 15-18 September, 2011
Abstract: Software development organisations are under heavy pressure to complete projects on time, within budget and with the appropriate level of quality, and many questions are asked when a project fails to meet any or all of these requirements. Over the years, much research effort has been spent to find ways to mitigate these failures, the reasons of which come from both within and outside the organisation's control. One possible risk of failure lies in human resource management and, since humans are the main asset of software organisations, getting the right team to do the job is critical. This paper proposes a procedure for software project managers to support their project scheduling and team staffing activities - two areas where human resources directly impact software development projects and management decisions - by adopting a genetic algorithm approach as an optimisation technique to help solve software project scheduling and team staffing problems.
URI: http://ktisis.cut.ac.cy/jspui/handle/10488/3840
ISSN: 18684238
DOI: 10.1007/978-3-642-23960-1_21
Rights: IFIP International Federation for Information Processing
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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