A Hybrid Grey Relational Analysis and Nondominated Sorting Genetic Algorithm-II for Project Portfolio Selection

Abstract EN

Project selection and formation of an optimal portfolio of selected projects are among the main challenges of project management.

For this purpose, several factors and indicators are simultaneously examined considering the terms and conditions of the decision problem.

Obviously, both qualitative and quantitative factors may influence the formation of a portfolio of projects.

In this study, the projects were first ranked using grey relational analysis to form an optimal portfolio of projects and to create an expert system for the final project selection.

Because of the fuzzy nature of the environmental risk of each project, the environmental risk was predicted and analyzed using the fuzzy inference system and failure mode and effect analysis based on fuzzy rules.

Then, the rank and risk of each project were optimized using a two-objective zero-one mathematical programming model considering the practical constraints of the decision problem through the nondominated sorting genetic algorithm-II (NSGA-II).

A case study was used to discuss the practical methodology for selecting a portfolio of projects.