nach oben

Soft Computing

Erschienen in:

11.06.2018 | Focus

Balancing strategic contributions and financial returns: a project portfolio selection model under uncertainty

verfasst von: Yuntao Guo, Lin Wang, Suike Li, Zhi Chen, Yin Cheng

Erschienen in: Soft Computing | Ausgabe 16/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This paper constructs a project portfolio selection model from the strategic perspective. Two goals are proposed for the portfolio to achieve, i.e., strategic contributions and financial returns. The uncertainties involved are addressed with fuzzy real options. Then, a modified multi-objective genetic algorithm is designed to determine the portfolios. Finally, a real case is provided to validate the model’s effectiveness. The results demonstrate that the proposed algorithm can optimize two objectives simultaneously and keep the plausible Pareto-optimal set which wins over the single-objective model solutions in achieving the shared value.

Vorheriger Artikel Project portfolio selection based on synergy degree of composite system

Nächster Artikel An optimal model using data envelopment analysis for uncertainty metrics in reliability

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Abbassi M, Ashrafi M, Sharifi Tashnizi E (2014) Selecting balanced portfolios of R&D projects with interdependencies: a cross-entropy based methodology. Technovation 34(1):54–63CrossRef

Alves MJ, Almeida M (2007) MOTGA: a multiobjective Tchebycheff based genetic algorithm for the multidimensional knapsack problem. Comput Oper Res 34(11):3458–3470MathSciNetCrossRefMATH

Arratia MNM, López IF, Schaeffer SE, Cruz-Reyes L (2016) Static R&D project portfolio selection in public organizations. Decis Support Syst 84:53–63CrossRef

Bednyagin D, Gnansounou E (2011) Real options valuation of fusion energy R&D programme. Energy Policy 39(1):116–130CrossRef

Bhattacharyya R, Kumar P, Kar S (2011) Fuzzy R&D portfolio selection of interdependent projects. Comput Math Appl 62(10):3857–3870MathSciNetCrossRefMATH

Birgisson I (2012) Project portfolio management in new product development organizations application of accepted PPM theories in practice (master’s thesis), Chalmers University of technology

Chiang IR, Nunez MA (2013) Strategic alignment and value maximization for IT project portfolios. Inf Technol Manag 14(2):143–157CrossRef

Chiranjit Changdar, Mahapatra GS, Pal Rajat Kumar (2015) An improved genetic algorithm based approach to solve constrained knapsack problem in fuzzy environment. Expert Syst Appl 42(4):2276–2286CrossRef

Cruz-Reyes L, Fernandez E, Sanchez P, Coello Coello CA, Gomez C (2017) Incorporation of implicit decision-maker preferences in multi-objective evolutionary optimization using a multi-criteria classification method. Appl Soft Comput J 50:48–57CrossRef

De Oliveira LL, Freitas AA, Tinós R (2018) Multi-objective genetic algorithms in the study of the genetic code’s adaptability. Inf Sci 425:48–61MathSciNetCrossRef

De Reyck B, Grushka-Cockayne Y, Lockett M, Calderini SR, Moura M, Sloper A (2005) The impact of project portfolio management on information technology projects. Int J Proj Manag 23(7):524–537CrossRef

Hassanzadeh F, Collan M, Modarres M (2012) A practical approach to R&D portfolio selection using the fuzzy pay-off method. IEEE Trans Fuzzy Syst 20(4):615–622CrossRef

Kalashnikov V, Benita F, López-Ramos F, Hernández-Luna A (2017) Bi-objective project portfolio selection in Lean Six Sigma. Int J Prod Econ 186:81–88CrossRef

Karsak E (2006) A generalized fuzzy optimization framework for R&D project selection using real options valuation. In: Computational science and its applications-ICCSA, pp 918–927

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 220:442–462CrossRef

Li D, Gu H, Zhang L (2013) A hybrid genetic algorithm-fuzzy c -means approach for incomplete data clustering based on nearest-neighbor intervals. Soft Comput 17(10):1787–1796CrossRef

Liesiö J, Salo A (2012) Scenario-based portfolio selection of investment projects with incomplete probability and utility information. Eur J Oper Res 217(1):162–172MathSciNetCrossRefMATH

Lin FT (2008) Solving the knapsack problem with imprecise weight coefficients using genetic algorithms. Eur J Oper Res 185(1):133–145CrossRefMATH

Mohagheghi V, Mousavi SM, Vahdani B (2015) A new optimization model for project portfolio selection under interval-valued fuzzy environment. Arab J Sci Eng 40(11):3351–3361MathSciNetCrossRefMATH

Nassif LN, Filho JCS, Nogueira JM (2013) Project portfolio selection in public administration using fuzzy logic. Proc Soc Behav Sci 74:41–50CrossRef

Perez-Escobedo JL, Azzaro-Pantel C, Pibouleau L (2012) Multiobjective strategies for New Product Development in the pharmaceutical industry. Comput Chem Eng 37:278–296CrossRef

Piroozfard H, Wong KY, Wong WP (2018) Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm. Resour Conserv Recycl 128:267–283CrossRef

Relich M, Pawlewski P (2017) A fuzzy weighted average approach for selecting portfolio of new product development projects. Neurocomputing 231:19–27CrossRef

Shu L, Jiang P, Zhou Q, Shao X, Hu J, Meng X (2018) An on-line variable fidelity metamodel assisted multi-objective genetic algorithm for engineering design optimization. Appl Soft Comput 66:438–448CrossRef

Tolga AÇ (2012) A real options approach for software development projects using fuzzy electre. J Mult Valued Logic Soft Comput 18:541–560

Wang J, Wang J, Hwang W (2007) A fuzzy set approach for R & D portfolio selection using a real options valuation model A fuzzy set approach for R & D portfolio selection using a real options valuation model. Omega 35:247–257CrossRef

Wang Q, Kilgour DM, Hipel KW (2011) Fuzzy real options for risky project evaluation using least squares Monte-Carlo simulation. IEEE Syst J 5(3):385–395

Xu XF, Zhang W, Li N, Xu HL (2015) A bi-level programming model of resource matching for collaborative logistics network in supply uncertainty environment. J Frankl Inst 352:3873–3884MathSciNetCrossRef

Xu XF, Hao J, Deng YR, Wang Y (2017) Design optimization of resource combination for collaborative logistics network under uncertainty. Appl Soft Comput 560(7):684–691CrossRef

Yan S, Ji X (2017) Portfolio selection model of oil projects under uncertain environment. Soft Comput. https://doi.org/10.1007/s00500-017-2619-2

Yassine AA, Mostafa O, Browning TR (2017) Scheduling multiple, resource-constrained, iterative, product development projects with genetic algorithms. Comput Ind Eng 107:39–56CrossRef

You CJ, Lee CKM, Chen SL, Jiao RJ (2012) A real option theoretic fuzzy evaluation model for enterprise resource planning investment. J Eng Technol Manag JET-M 29(1):47–61CrossRef

Titel: Balancing strategic contributions and financial returns: a project portfolio selection model under uncertainty
verfasst von: Yuntao Guo
Lin Wang
Suike Li
Zhi Chen
Yin Cheng
Publikationsdatum: 11.06.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 16/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3294-7

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 16/2018

Managerial compensation and research and development investment in a two-period agency setting

Credibility support vector machines based on fuzzy outputs

Project portfolio selection based on synergy degree of composite system

The coordination mechanisms of emergency inventory model under supply disruptions

Case-based reasoning with optimized weight derived by particle swarm optimization for software effort estimation

Evaluation research on commercial bank counterparty credit risk management based on new intuitionistic fuzzy method