Hamidreza Shahabifard; Behrouz Afshar-nadjafi
Abstract
In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems ...
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In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems list, so a genetic based meta-heuristic algorithm isproposed to tackle the developed model. In the proposed algorithm besidecommon operators of genetic algorithms such as crossover & mutation, someintelligent operators are utilized for local search in computed resources andshifting the activities with negative cash flows. The key parameters of thealgorithm are calibrated using Taguchi method to accelerate convergence ofthe proposed algorithm. Then, the algorithm is used to solve 90 testproblems consisting 30 small-scale, 30 middle-scale and 30 large scaleproblems to examine the algorithm’s performance. It is observed that, insmall problems, the obtained solutions from the proposed genetic algorithmhave been comparably better than the local optimum solutions stemmedfrom Lingo software. On the other hand, for the middle and large sizeproblems which there is no local optimum available within the limited CPUtime, robustness of the proposed algorithm is appropriate
