Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Software Risk Management: Principles and Practices
IEEE Software
Dynamic rescheduling that simultaneously considers efficiency and stability
Computers and Industrial Engineering
METRICS '04 Proceedings of the Software Metrics, 10th International Symposium
requirements uncertainty: influencing factors and concrete improvements
Proceedings of the 27th international conference on Software engineering
ICSM '05 Proceedings of the 21st IEEE International Conference on Software Maintenance
Emphasizing Human Capabilities in Software Development
IEEE Software
Software project management with GAs
Information Sciences: an International Journal
Stability-oriented evaluation of rescheduling strategies, by using simulation
Computers in Industry
Staffing a software project: A constraint satisfaction and optimization-based approach
Computers and Operations Research
Time-line based model for software project scheduling with genetic algorithms
Information and Software Technology
Match-Up Strategies for Job Shop Rescheduling
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
A Task Allocation Optimizer for Software Construction
IEEE Software
Value-Based Multiple Software Projects Scheduling with Genetic Algorithm
ICSP '09 Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes
Achieving On-Time Delivery: A Two-Stage Probabilistic Scheduling Strategy for Software Projects
ICSP '09 Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes
Multi-objective scheduling of dynamic job shop using variable neighborhood search
Expert Systems with Applications: An International Journal
ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
Uncertainty handling in tabular-based requirements using rough sets
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Bayesian networks in software maintenance management
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
On mobility of software processes
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
A process-agent construction method for software process modeling in SoftPM
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
Experience modeling and analyzing medical processes: UMass/baystate medical safety project overview
Proceedings of the 1st ACM International Health Informatics Symposium
Cooperative co-evolutionary optimization of software project staff assignments and job scheduling
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Do we need to handle every temporal violation in scientific workflow systems?
ACM Transactions on Software Engineering and Methodology (TOSEM)
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Good resource scheduling plays a pivotal role in successful software development projects. However, effective resource scheduling is complicated by such disruptions as requirements changes, urgent bug fixing, incorrect or unexpected process execution, and staff turnover. Such disruptions demand immediate attention, but can also impact the stability of other ongoing projects. Dynamic resource rescheduling can help suggest strategies for addressing such potentially disruptive events by suggesting how to balance the need for rapid response and the need for organizational stability. This paper proposes a multi-objective rescheduling method to address the need for software project resource management that is able to suggest strategies for addressing such disruptions. A genetic algorithm is used to support rescheduling computations. Examples used to evaluate this approach suggest that it can support more effective resource management in disruption-prone software development environments.