Abstract
This paper involves the resource constrained project robust scheduling problem where the objective is to maximize the robustness of the baseline schedule under the constraints of resources and project deadline. On the basis of the identification of the problem, the optimization model is constructed. Then, for the NP-hardness of the problem, the two versions of variable neighborhood search (VNS), i.e., the hybrid VNS and the parallel VNS, are developed to solve the problem. To evaluate the performance of the two VNS methods, a computational experiment is conducted based on a set of data consisting of 50 instances generated randomly. The results show that the developed algorithms can solve the problem with an acceptable computational time. With the increase of the problem scale, the hybrid VNS performs better while the parallel VNS becomes worse.
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