This study considers the problem of resource constrained project scheduling to maximise the net present value. A number of tasks must be scheduled within a fixed time horizon. Tasks may have precedences between them and they use a number of common resources when executing. For each resource, there is a limit, and the cumulative resource requirements of all tasks executing at the same time must not exceed the limits. To solve this problem, we develop a hybrid of Construct, Merge, Solve and Adapt (CMSA) and Ant Colony Optimisation (ACO). The methods are implemented in a parallel setting within a multi-core shared memory architecture. The results show that the proposed algorithm outperforms the previous state-of-the-art method, a hybrid of Lagrangian relaxation and ACO.
CITATION STYLE
Thiruvady, D., Blum, C., & Ernst, A. T. (2019). Maximising the net present value of project schedules using CMSA and parallel ACO. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11299 LNCS, pp. 16–30). Springer Verlag. https://doi.org/10.1007/978-3-030-05983-5_2
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