Project portfolio selection and scheduling under a fuzzy environment

• Published in: Memetic computing Vol. 11; no. 4; pp. 391 - 406
• Main Authors: Zhang, Xiaoxiong, Hipel, Keith W., Tan, Yuejin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2019; Springer Nature B.V
• Subjects: Algorithms; Applications of Mathematics; Artificial Intelligence; Bioinformatics; Complex Systems; Control; Engineering; Evolutionary algorithms; Fuzzy logic; Fuzzy sets; Gaussian process; Mathematical and Computational Engineering; Mathematical models; Mechatronics; Multiple objective analysis; Project management; Regular Research Paper; Risk analysis; Robotics; Scheduling; Multi-objective optimization; Project portfolio selection and planning; Gaussian process; Fuzzy numbers; Inverse modeling
• ISSN: 1865-9284; 1865-9292
• DOI: 10.1007/s12293-019-00282-5

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.