Abstract
The management of a project portfolio is a complex decision process because it encompasses the achievement of multiple objectives. A critical point that increases the complexity in the decision-making process of a portfolio manager is the allocation of human resources to manage the projects of the portfolio, project managers, which is crucial to the organization’s performance. In this case, the project manager can manage more than one project simultaneously and it is necessary to assign project managers to the projects, considering that project activities have an amount of work to be accomplished. The main objective of this work was to provide support for this capacity management problem, which aims to provide an easier decision-making process for the capacity management of an industrialization project portfolio. Therefore, it was developed: a hybrid model that creates a schedule respecting the resource constraints and the established due dates; a recommendation system that considers project managers’ allocation and projects requirements; and, an automatic status report that allows identifying the project portfolio capacity usage.
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References
Abrantes, R., Figueiredo, J.: Resource management process framework for dynamic NPD portfolios. Int. J. Proj. Manag. 33, 1274–1288 (2015). https://doi.org/10.1016/j.ijproman.2015.03.012
Oh, J., Yang, J., Lee, S.: Managing uncertainty to improve decision-making in NPD portfolio management with a fuzzy expert system. Expert Syst. Appl. 39, 9868–9885 (2012). https://doi.org/10.1016/j.eswa.2012.02.164
Manole, A.L., Grabara, I.: Methodologies and visualization tools of effective project management. Polish J. Manag. Stud. 14, 137–149 (2016). https://doi.org/10.17512/pjms.2016.14.2.13
Perrotta, D., Araújo, M., Fernandes, G., Tereso, A., Faria, J.: Towards the development of a methodology for managing industrialization projects. Procedia Comput. Sci. 121, 874–882 (2017). https://doi.org/10.1016/j.procs.2017.11.113
Chirumalla, K.: Managing product introduction projects in operations: key challenges in heavy-duty vehicle industry. J. Mod. Proj. Manag. 5, 108–118 (2018). https://doi.org/10.19255/JMPM01512
Radujković, M., Sjekavica, M.: Project management success factors. Procedia Eng. 196, 607–615 (2017). https://doi.org/10.1016/j.proeng.2017.08.048
Ponsteen, A., Kusters, R.J.: Classification of human- and automated resource allocation approaches in multi-project management. Procedia Soc. Behav. Sci. 194, 165–173 (2015). https://doi.org/10.1016/j.sbspro.2015.06.130
Tian, X., Yuan, S.: Genetic algorithm parameters tuning for resource-constrained project scheduling problem. In: AIP Conference Proceedings, p. 040059 (2018)
Chakrabortty, R.K., Sarker, R., Essam, D.L.: A comparative study of different integer linear programming approaches for resource-constrained project scheduling problems. Presented at the (2018)
Kolisch, R., Hartmann, S.: Experimental investigation of heuristics for resource-constrained project scheduling: an update. Eur. J. Oper. Res. 174, 23–37 (2006). https://doi.org/10.1016/j.ejor.2005.01.065
Borak, S., Karl, W.: Matheuristics. Springer, Boston (2010)
Artigues, C., Brucker, P., Knust, S., Koné, O., Lopez, P., Mongeau, M.: A note on “event-based MILP models for resource-constrained project scheduling problems”. Comput. Oper. Res. 40, 1060–1063 (2013). https://doi.org/10.1016/j.cor.2012.10.018
Maniezzo, V., Stutzle, T.: Matheuristics 2016 - Proceedings of the Sixth International Workshop on Model-based Metaheuristics. IRIDIA, Bruxelles (2016)
Saunders, M., Lewis, P., Thornhill, A.: Research Methods for Business Students (2016)
Shrestha, A., Cater-Steel, A., Toleman, M., Rout, T.: Benefits and relevance of International Standards in a design science research project for process assessments. Comput. Stand. Interfaces. 60, 48–56 (2018). https://doi.org/10.1016/j.csi.2018.04.011
Wang, D., Wan, K., Song, X., Liu, Y.: Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness. Energy Econ. 78, 109–128 (2019). https://doi.org/10.1016/j.eneco.2018.11.004
Tereso, A., Araújo, M., Elmaghraby, S.: Adaptive resource allocation in multimodal activity networks. Int. J. Prod. Econ. 92, 1–10 (2004). https://doi.org/10.1016/j.ijpe.2003.09.005
Peck, R., Devore, J.L.: Statistics - The exploration & Analysis of data. Brooks/Cole (2010)
Keser, İ.K., Kocakoç, İ.D., Şehirlioğlu, A.K.: A new descriptive statistic for functional data: functional coefficient of variation. Alphanumeric J. 4, (2016). https://doi.org/10.17093/aj.2016.4.2.5000185408
Acknowledgements
This work is supported by: European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 39479; Funding Reference: POCI-01-0247-FEDER-39479].
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Lima, C., Tereso, A., Araújo, M. (2020). A Capacity Management Tool for a Portfolio of Industrialization Projects. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1159. Springer, Cham. https://doi.org/10.1007/978-3-030-45688-7_8
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