Abstract
In this paper, we present a new genetic algorithm for the resource-constrained project scheduling problem with discounted cash flows and investigate the trade-off between a project’s net present value and its corresponding makespan. We consider a problem formulation where the pre-specified project deadline is not set as a hard constraint, but rather as a soft constraint that can be violated against a certain penalty cost. The genetic algorithm creates children from parents taken from three different populations, each containing relevant information about the (positive or negative) activity cash flows. We have tested various parent selection methods based on four crossover operators taken from literature and present extensive computational results.
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Vanhoucke, M. (2009). A Genetic Algorithm for Net Present Value Maximization for Resource Constrained Projects. In: Cotta, C., Cowling, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2009. Lecture Notes in Computer Science, vol 5482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01009-5_2
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DOI: https://doi.org/10.1007/978-3-642-01009-5_2
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