Skip to main content

Interdependent Projects Selection with Preference Incorporation

  • Chapter
  • First Online:
New Perspectives on Applied Industrial Tools and Techniques

Abstract

The Project Portfolio Problem (PPP) has been solved through different approaches. The success of some of them is related to a proper application of the decision-maker’s preferences, and a correct identification of organization’s resource practices and conditions. However, there are still a small number of classes of PPP that have been solved using these approaches, and there is also a need for increasing them. Due to this situation, the present research develops a strategy, based on ant colony optimization that incorporates the decision-maker’s preferences into the solution of a case of PPP under conditions of synergy, cannibalization, redundancy, and with interactions between projects. The algorithm was experimentally tested, and the results show a good performance of it over a random set of instances.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Boardman AE, Greenberg DH, Vining AR, Weimer DL (2006) Cost-benefit analysis: concepts and practice. Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  • Brans J, Mareschal B (2005) Promethee methods. In: Greco S (ed) Multiple criteria decision analysis: state of the art surveys. International series in operations research & management science, Springer, New York, pp 163–190

    Google Scholar 

  • Carazo AF, Gómez T, Molina J et al (2010) Solving a comprehensive model for multiobjective project portfolio selection. Comput Oper Res 37(4):630–639

    Article  MathSciNet  MATH  Google Scholar 

  • Chaharsooghi SK, Kermani AHM (2008) An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP). Appl Math Comput 200:167–177

    MathSciNet  MATH  Google Scholar 

  • Coello CAC (1999) An updated survey of evolutionary multiobjective optimization techniques: state of the art and future trends. In: Proceedings of the 1999 congress on evolutionary computation, CEC 99, IEEE, pp 3–13

    Google Scholar 

  • Covantes E, Fernandez E, Navarro J (2013) Robustness analysis of a MOEA-based elicitation method for outranking model parameters. In: 2013 10th international conference on electrical engineering, computing science and automatic control (CCE), IEEE, pp 209–214

    Google Scholar 

  • Cruz L, Fernandez E, Gomez C et al (2014) Many-objective portfolio optimization of interdependent projects with “a priori” incorporation of decision-maker preferences. Appl Math 8:1517–1531

    Google Scholar 

  • Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, New York

    Google Scholar 

  • Del Sagrado J, del Águila IM, Orellana FJ (2015) Multi-objective ant colony optimization for requirements selection. Empir Softw Eng 20:577–610. doi:10.1007/s10664-013-9287-3

    Article  Google Scholar 

  • Doerner K, Gutjahr WJ, Hartl RF et al (2004) Pareto ant colony optimization: a metaheuristic approach to multiobjective portfolio selection. Ann Oper Res 131:79–99

    Article  MathSciNet  MATH  Google Scholar 

  • Doerner KF, Gutjahr WJ, Hartl RF et al (2006) Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection. Eur J Oper Res 171:830–841

    Article  MathSciNet  MATH  Google Scholar 

  • Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1:53–66

    Article  Google Scholar 

  • Doumpos M, Marinakis Y, Marinaki M, Zopounidis C (2009) An evolutionary approach to construction of outranking models for multicriteria classification: the case of the ELECTRE TRI method. Eur J Oper Res 199:496–505

    Article  MATH  Google Scholar 

  • Duan P, Yong AI (2016) Research on an improved ant colony optimization algorithm and its application. Int J Hybrid Inf Technol 9(4):223–234. doi:10.14257/ijhit.2016.9.4.20

  • Fernandez E, Lopez E, Bernal S et al (2010) Evolutionary multiobjective optimization using an outranking-based dominance generalization. Comput Oper Res 37:390–395

    Article  MATH  Google Scholar 

  • Fernandez E, Lopez E, Lopez F, Coello CAC (2011) Increasing selective pressure towards the best compromise in evolutionary multiobjective optimization: the extended NOSGA method. Inf Sci (Ny) 181:44–56

    Article  MathSciNet  MATH  Google Scholar 

  • Fernandez E, Gomez C, Rivera G, Cruz L (2014) Optimización de cartera de proyectos con financiamiento parcial mediante un metaheurísti-co enriquecido con programación lineal entera e incorporación de preferencias. In: Rios R, Camacho J, Gonzalez J, Laguna M (eds) Recent advances in theory, methods and practice of operations research. Latin-Iberian-American Operations Research Society, pp 259–302

    Google Scholar 

  • Fernandez E, Gomez C, Rivera G, Cruz-Reyes L (2015) Hybrid metaheuristic approach for handling many objectives and decisions on partial support in project portfolio optimisation. Inf Sci (Ny) 315:102–122

    Article  MathSciNet  Google Scholar 

  • Fernández González E, López Cervantes E, Navarro Castillo J, Vega López I (2011) Aplicación de metaheurísticas multiobjetivo a la solución de problemas de cartera de proyectos públicos con una valoración multidimensional de su impacto. Gestión y política pública 20:381–432

    Google Scholar 

  • Georgia Department of Transportation (2010) Project list and final investment report

    Google Scholar 

  • Georgia Department of Transportation (2012a) Central Savannah River Area, unconstrained project list by county

    Google Scholar 

  • Georgia Department of Transportation (2012b) Heart of Georgia, Altamaha unconstrained project list by county

    Google Scholar 

  • Georgia Department of Transportation (2012c) River Valley Area, unconstrained project list by county

    Google Scholar 

  • Gutjahr WJ, Katzensteiner S, Reiter P et al (2010) Multi-objective decision analysis for competence-oriented project portfolio selection. Eur J Oper Res 205:670–679

    Article  MathSciNet  MATH  Google Scholar 

  • Jacquet-Lagreze E, Siskos Y (2001) Preference disaggregation: 20 years of MCDA experience. Eur J Oper Res 130:233–245

    Article  MATH  Google Scholar 

  • Khalili-Damghani K, Sadi-Nezhad S, Lotfi FH, Tavana M (2013) A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection. Inf Sci (Ny) 220:442–462

    Article  Google Scholar 

  • Knowles JD, Corne DW (2000) M-PAES: a memetic algorithm for multiobjective optimization. IEEE international conference on evolutionary computation, pp 325–332. doi:10.1109/cec.2000.870313, citeulike-article-id:8823683

  • Liesiö J, Mild P, Salo A (2007) Preference programming for robust portfolio modeling and project selection. Eur J Oper Res 181:1488–1505

    Article  MATH  Google Scholar 

  • Marakas G (2002) Decision support systems and megaputer. Prentice Hall, Upper Saddle River, New Jersey

    Google Scholar 

  • Mild P, Liesiö J, Salo A (2015) Selecting infrastructure maintenance projects with robust portfolio modeling. Decis Support Syst 77:21–30

    Article  Google Scholar 

  • Mousa AA, El_Desoky IM (2013) Stability of Pareto optimal allocation of land reclamation by multistage decision-based multipheromone ant colony optimization. Swarm Evol Comput 13:13–21

    Google Scholar 

  • Rădulescu CZ, Rădulescu M (2001) Project portfolio selection models and decision support. Stud Inform Control 10:275–286

    Google Scholar 

  • Rivera G, Gomez C, Fernandez E, Cruz L, Castillo O, Bastiani S (2012a) Handling of synergy into an algorithm for project portfolio selection. In: Castillo O, Melin P, Kacprzyk J (eds) Recent advances on hybrid intelligent systems, Springer, Berlin, pp 417–430

    Google Scholar 

  • Rivera G, Gómez C, Cruz L et al (2012b) Solution to the social portfolio problem by evolutionary algorithms. Int J 21–30

    Google Scholar 

  • Roy B (1996) Multicriteria methodology for decision aiding, volume 12 of nonconvex optimization and its applications. Kluwer Academic, Dordrecht

    Google Scholar 

  • Stummer C, Heidenberger K (2003) Solving a comprehensive model for multiobjective project portfolio selection. IEEE Trans Eng Manage 50:175–183

    Google Scholar 

  • U.S. Government Printing Office (2012) Budget of the United States government

    Google Scholar 

  • Zhang Z, Gao C, Liu Y, Qian T (2014) A universal optimization strategy for ant colony optimization algorithms based on the Phsysarum-inspired mathematical model. Bioinspiration ssBiomimetics 9:36006

    Article  Google Scholar 

Download references

Acknowledgements

This work has been partially supported by PRODEP and the following projects: (a) CONACYT Project 236154; (b) Project 3058 from the program Catedras CONACYT; and, (c) Project 269890 from CONACYT networks.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Claudia G. Gomez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Gomez, C.G., Cruz-Reyes, L., Rivera, G., Rangel-Valdez, N., Morales-Rodriguez, M.L., Perez-Villafuerte, M. (2018). Interdependent Projects Selection with Preference Incorporation. In: García-Alcaraz, J., Alor-Hernández, G., Maldonado-Macías, A., Sánchez-Ramírez, C. (eds) New Perspectives on Applied Industrial Tools and Techniques. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-56871-3_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-56871-3_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56870-6

  • Online ISBN: 978-3-319-56871-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics