A TYPE-2 FUZZY OPTIMIZATION MODEL FOR PROJECT PORTFOLIO SELECTION AND SCHEDULING INCORPORATING PROJECT INTERDEPENDENCY AND SPLITTING

Samaneh Zolfaghari,Jurgita Antuchevičienė,Seyed Meysam Mousavi

doi:10.3846/tede.2021.14652

Samaneh Zolfaghari, Jurgita Antuchevičienė + Show 1 more

Open Access

https://doi.org/10.3846/tede.2021.14652

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Abstract

This paper presents a new optimization model and a new interval type-2 fuzzy solution approach for project portfolio selection and scheduling (PPSS) problem, in which split of projects and re-execution are allowable. Afterward, the approach is realized as a multi-objective optimization that maximizes total benefits of projects concerning economic concepts by considering the interest rate and time value of money and minimizes the tardiness value and total number of interruptions of chosen projects. Besides, budget and resources limitation, newfound relations are proposed to consider dependency relationships via a synergy among projects to solve PPSS problem hiring interval type-2 fuzzy sets. For validation of the model, numerical instances are provided and solved by a new extended procedure based on fuzzy optimistic and pessimistic viewpoints regarding several situations. In the end, their results are studied. The results show that it is more beneficial when projects are allowed to be split.

Highlights

Project portfolio selection and scheduling (PPSS) tries to regard proper candidates from a set of projects and make a thorough improvement scheme
A new optimization model is developed for the PPSS problem by splitting over several intervals during the planning horizon and considering interdependency among projects in terms of synergy where selected projects can be implemented on the flexible due date
This study presents an optimization approach for the PPSS issue where two different concerns are jointly considered: how to select and how to schedule well-organized project portfolios

Summary

Introduction

Project portfolio selection and scheduling (PPSS) tries to regard proper candidates from a set of projects and make a thorough improvement scheme. Fuzzy sets theory is a common tool to handle non-probabilistic uncertainty in. Zolfaghari et al A type-2 fuzzy optimization model for project portfolio selection and scheduling. Involving more uncertainty sources causes more complexity in modeling (Haghighi et al, 2019b; Peng & Huang, 2020). Because of various kinds of complexities in reality, project managers cannot always define the exact membership function to show an uncertain boundary by type-1 fuzzy sets (T1FSs). Type-2 fuzzy set (T2FS) is used to pass on the vulnerability in the membership function and enables further degrees of freedom as compared to T1FS, by regarding remarkable engineering applications (e.g., Mirnezami et al, 2020; Mohagheghi et al, 2020; Haghighi et al, 2019a; Eshghi et al, 2019; Dorfeshan et al, 2019)

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