An Ant Colony Algorithm for Improving the Net Present Values of Resource Constrained Projects
نویسنده
چکیده
An ant colony algorithm is proposed to improve the net present values of resource-constrained projects since the net present value is a critical criterion for a project with a long time span and considerable cash flows. The algorithm adaptively adjusts the allocation of scarce resources according to the pheromone generated by artificial ants in the previous iterations so as to maximize the project’s net present value. The crossover operation, inverse mutation and elitist strategy are applied to accelerate the searching for better project schedules, and the backward scheduling technique is adopted to improve the net present value further. The experimental test results show that the proposed algorithm significantly improves the net present values of resource-constrained projects.
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