Document Type : Research Paper
Authors
Abstract
In this paper, a mathematical model is proposed for project portfolio
selection and resource availability cost problem to scheduling activities in
order to maximize net present value of the selected projects preserving
precedence and resource constraints. Since the developed model belongs to
NP-hard problems list, so a genetic based meta-heuristic algorithm is
proposed to tackle the developed model. In the proposed algorithm beside
common operators of genetic algorithms such as crossover & mutation, some
intelligent operators are utilized for local search in computed resources and
shifting the activities with negative cash flows. The key parameters of the
algorithm are calibrated using Taguchi method to accelerate convergence of
the proposed algorithm. Then, the algorithm is used to solve 90 test
problems consisting 30 small-scale, 30 middle-scale and 30 large scale
problems to examine the algorithm’s performance. It is observed that, in
small problems, the obtained solutions from the proposed genetic algorithm
have been comparably better than the local optimum solutions stemmed
from Lingo software. On the other hand, for the middle and large size
problems which there is no local optimum available within the limited CPU
time, robustness of the proposed algorithm is appropriate
Keywords
schedule maintenance policy based on multiple-criteria decision-making.
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