Project Portfolio Selection and Scheduling with Resource Allocation, Synergies, and Project Divisibility

Author:

Arratia-Martinez Nancy M.1ORCID,Hernandez-Gonzalez Nelly M.1ORCID,Lopez-Irarragorri Fernando2ORCID

Affiliation:

1. Universidad de las Américas Puebla, Ex-Hacienda Santa Catarina Mártir S/N, 72810, San Andrés Cholula, Puebla, Mexico

2. Universidad Autónoma de Nuevo León, Pedro de Alba S/N, Niños Héroes, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León 66455, Mexico

Abstract

A project portfolio can be defined as a set of project proposals that are selected according to one or more criteria by a decision-maker (individual or group). Regularly, the portfolio selection involves different decision problems, among those evaluation, selection, scheduling, and resource allocation. In published scientific literature, these problems have been addressed mainly separately giving as a result suboptimal solutions (portfolios). In addition, elements as partial allocation and project representation through tasks constitute relevant characteristics in practice that remain unaddressed in depth. The proposal of this research is to integrate the project selection and project scheduling, incorporating all relevant elements of both decision problems through the scheduling of tasks allowing to determine when the task will be funded and executed. The main impact of precedence rules at the task level in the portfolio is also studied. In this work, Project Portfolio Selection and Scheduling Problem (PPSS) is studied and solved through a new mixed-integer linear programming (MILP) model. The model incorporates renewable and nonrenewable resource allocation, along with partial and total funding policies, project divisibility, and interdependences. Scheduling is integrated into the model, both at the project level and at the project task level, which allows scheduling in noncontiguous periods. Small instances (up to 64 projects) and medium instances (up to 128 projects) were solved optimally in very short times. The relationship between the quality of near-optimal solutions and the solution computing time by modifying the parameters of the solver employed was researched. No significant change in the solution’s quality was perceived, but a significant reduction in solution computing time was achieved. Furthermore, the main effects of precedence rules on solution times and portfolio impact were studied. Results show that even if few precedence rules were introduced, the resource allocation of tasks changed significantly, even though the portfolio impact or the number of projects of the selected portfolios remains the same.

Funder

Universidad de las Américas Puebla

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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