Modelling adaptive multi-agent manufacturing control with discrete event system formalism
International Journal of Systems Science
Software project management with GAs
Information Sciences: an International Journal
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Time-line based model for software project scheduling with genetic algorithms
Information and Software Technology
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
Handling alternative activities in resource-constrained project scheduling problems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Extending the RCPSP for modeling and solving disruption management problems
Applied Intelligence
A Neurogenetic approach for the resource-constrained project scheduling problem
Computers and Operations Research
Chaos-based improved immune algorithm (CBIIA) for resource-constrained project scheduling problems
Expert Systems with Applications: An International Journal
A dynamic clonal selection algorithm for project optimization scheduling
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Handling airport ground processes based on resource-constrained project scheduling
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
GA-Based resource-constrained project scheduling with the objective of minimizing activities' cost
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
A multi-agent genetic algorithm for resource constrained project scheduling problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A New Genetic Algorithm for the RCPSP in Large Scale
International Journal of Applied Evolutionary Computation
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The single-mode, single-project, resource-constrained project-scheduling problem is solved by an evolutionary algorithm. The design of this algorithm is presented. Results of a computational study on two sets of benchmark problems, the first consisting of 330 problem instances and the second 2040, are presented. These results show that the proposed algorithm is effective in terms of the number of times it achieves both the best-known solutions and the average error with respect to these solutions, particularly given that the best-known solutions have been compiled from various sources, using a variety of algorithms. Moreover, the computation time requirements are quite modest