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Project portfolio selection and scheduling under a fuzzy environment

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Abstract

The problem of integrated project portfolio selection and scheduling (PPSS) is among the most important and highly pursed subjects in project management. In this study, a mathematical model and algorithm are designed specifically to assist decision makers decide which projects are to be chosen and when these projects are to be undertaken. More specifically, the PPSS problem is first formulated as a nonlinear multi-objective model with simultaneous consideration of benefit and risk factors. Due to the complexity and uncertainty involved in most real life situations, fuzzy numbers are incorporated into the model, which can provide decision makers with more flexibility. Then, an inverse modeling based multi-objective evolutionary algorithm using a Gaussian Process is presented to obtain the Pareto set. Finally, an illustrative example is used to demonstrate the high efficacy of the foregoing approach, which can provide decision makers with valuable insights into the PPSS process. The proposed algorithm is found to be more effective compared with two other popular algorithms.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants 71690233, 71501182, and 71571185. The authors would like to thank the editor and three anonymous reviewers for their constructive comments that helped us to improve the quality of this paper.

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Correspondence to Xiaoxiong Zhang.

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Zhang, X., Hipel, K.W. & Tan, Y. Project portfolio selection and scheduling under a fuzzy environment. Memetic Comp. 11, 391–406 (2019). https://doi.org/10.1007/s12293-019-00282-5

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