Decision and Planning in Research and Development

  • Chapter
Practical Applications of Fuzzy Technologies

Part of the book series: The Handbooks of Fuzzy Sets Series ((FSHS,volume 6))

Abstract

The importance of research and development has been increasing steadily during the last decades and is still growing. As a consequence, methods and tools which can support the R&D planning and decision process also become more numerous and sophisticated. This main chapter gives an overview over important methods and reviews the literature in this area. Special attention is given to the modeling of different kinds of uncertainty using fuzzy logic which is particularly important in R&D planning. A broad spectrum of fuzzy approaches is used to support in research and development decision making.

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Abecker, A.; Bernardi, A.; Hinkelmann, K.; Kühn, O.; Sintek, M. (1998): Toward a Technology for Organizational Memories, in: IEEE Intelligent Systems, May/June 1998, pp. 40–48.

    Google Scholar 

  • Altrock, C. von, (1993): Fuzzy Logic — Technologie, Band 1, München.

    Google Scholar 

  • Anandalingam, G.; Olsson, C.E. (1989): A multi-stage multi-attribute decision model for project selection, in: European Journal of Operational Research 43, pp. 271–283.

    Google Scholar 

  • Baker, N.; Freeland, J. (1975): Recent advances in R&D benefit measurement and project selection methods, in: Management Science 21, No. 10, pp. 1164–1175.

    Google Scholar 

  • Baker, N.R.; Green, S.G.; Bean, A.S. (1986): The need for strategic balance in R&D project portfolios, in: Research Management 29, pp. 38–43.

    Google Scholar 

  • Bard, J.F. (1986): Evaluating space station applications of automation and robotics, in: IEEE Transactions on Engineering Management 33, No. 2, pp. 102–111.

    Google Scholar 

  • Bard, J.F.; Balachandra, R.; Kaufmann, P.E. (1988): An interactive approach to R&D project selection and termination, in: IEEE Transactions on Engineering Management 35, No. 3, pp. 139–146.

    Google Scholar 

  • Bellman, R.E.; Zadeh, L.A. (1970): Decision-making in a fuzzy environment, in: Management Science 17, No. 4, pp. 141–164.

    Google Scholar 

  • Booker, J.M.; Bryson, M.C. (1985): Decision analysis in project management: An overview, in: IEEE Transactions on Engineering Management 32, No. 1, pp. 1–9.

    Google Scholar 

  • Borisov, A.; Naglis, L. (1985): Multi-criteria choice of alternatives in an expert system for computer-aided design of industrial robot installations, in: Fuzzy Sets and Systems 16, pp. 93–101.

    Google Scholar 

  • Brockhoff, K. (1994): Forschung und Entwicklung: Planung und Kontrolle, München, Wien, 4., rev. ed.

    Google Scholar 

  • Brockhoff, K.; Chakrabarti, A.K. (1988): R&D/marketing linkage and innovation strategy: Some West German experience, in: IEEE Transactions on Engineering Management 35, No. 3, pp. 167–174.

    Google Scholar 

  • Chanas, S.; Kamburowski, J. (1981): The use of fuzzy variables in PERT, in: Fuzzy Sets and Systems 5, pp. 11–19.

    Google Scholar 

  • Chang, P.-L.; Chen, Y.-C. (1994): A fuzzy multi-criteria decision making method for technology transfer strategy selection in biotechnology, in: Fuzzy Sets and Systems 63, pp. 131–139.

    Google Scholar 

  • Coffin, M.A.; Taylor, B.W. III (1996): Multiple criteria R&D project selection and scheduling using fuzzy logic, in: Computers and Operations Research 23, No. 3, pp. 207–220.

    Google Scholar 

  • Cooper, R.G. (1994): Perspective: Third-generation new product processes, in: J. Prod. Innov. Manag. 11, pp. 3–14.

    Google Scholar 

  • Czajkowski, A.F.; Jones, S. (1986): Selecting interrelated R&D projects in space technology planning, in: IEEE Transactions on Engineering Management 33, No. 1, pp. 17–24.

    Google Scholar 

  • Danila, N.V. (1985): Evaluating pharmaceutical R&D, in: Mar, B.W., Newell, W.T. and Saxberg, B.O. (eds.): Managing High Technology, Amsterdam, pp. 25–40.

    Google Scholar 

  • Darzentas, J.; Darzentas, J.; Spyrou, T. (1994): Fuzzy reasoning and system thinking in a decision aid for designers, in: EUFIT ’94, Second European Congress on Intelligent Techniques and Soft Computing, Aachen, pp. 1609–1618.

    Google Scholar 

  • DePorter, E.L.; Ellis, K.P. (1990): Optimization of project networks with goal programming and fuzzy linear programming, in: Computers and Industrial Engineering 19, pp. 500–504.

    Google Scholar 

  • Dias, O.P. Jr. (1988): The R&D project selection problem with fuzzy coefficients, in: Fuzzy Sets and Systems 26, pp. 299–316.

    Google Scholar 

  • Dubois, D.; Prade, H. (1988): Possibility Theory: An Approach to Computerized Processing of Uncertainty, New-York.

    MATH  Google Scholar 

  • Eldukair, Z.A.; Ayyub, B.M. (1992): Multi-attribute fuzzy decisions in construction strategies, in: Fuzzy Sets and Systems 46, pp. 155–165.

    Google Scholar 

  • Eversheim, W.; Bochtler, W.; Laufenberg, L. (1994): Methods and models for integrated modelling of product and processes, in: Production Engineering 1/2, pp. 173–176.

    Google Scholar 

  • Eversheim, W.; Derichs, T.; Roggatz, A.; Zimmermann, H.-J. (1996): Management of uncertain information in simultaneous engineering, in: Sebastian, H.-J., Antonsson, E.K. (eds.): Fuzzy Sets in Engineering Design and Configuration, Boston, London, Dordrecht, pp. 233–250.

    Chapter  Google Scholar 

  • Eversheim, W.; Roggatz, A.; Zimmermann, H.-J.; Derichs, T. (1997): Information management for concurrent engineering, in: European Journal of Operational Research 100, No. 2, pp. 253–265.

    Google Scholar 

  • Fox, G.E.; Baker, N.R.; Bryant, J.L. (1984): Economic models for R and D project selection in the presence of project interactions, in: Management Science 30, No. 7, pp. 890–902.

    Google Scholar 

  • Frame, J.D. (1983): Quantitative indicators for evaluation of basic research programs/projects, in: IEEE Transactions on Engineering Management 30, No. 3, pp. 106–111.

    Google Scholar 

  • Gear, T.E.; Cowie, G.C. (1980): A note on modeling project interdependence in research and development, in: Decision Science 11, pp. 738–748.

    Google Scholar 

  • Geidel, J. (1990): Project scheduling with fuzzy data, in: Methods of Operations Research 62, pp. 339–347.

    Google Scholar 

  • Geoffrion, A.M. (1989): Computer-based modeling environments, in: European Journal of Operational Research 41, pp. 33–45.

    Google Scholar 

  • Glover, F.; Greenberg, H.J. (1989): New approaches for heuristic search: A bilateral linkage with artificial intelligence, in: European Journal of Operational Research 39, pp. 119–130.

    Google Scholar 

  • Graham, R. J. (1985), The role of network techniques in team building for project management, in: Dean, B.V. (ed.), Project Management: Methods and Studies, Amsterdam, pp. 163–171.

    Google Scholar 

  • Green Hall, N. (1993): A Fuzzycalc implementation of STRATASSIST - A DSS for strategic planners, in: EUFIT ’93 - First European Congress on Fuzzy and Intelligent Technologies, Aachen, September 7–10, pp. 547–551.

    Google Scholar 

  • Hapke, M.; Jaszkiewicz, A.; Slowinski, R. (1994): Fuzzy project scheduling system for software development, in: Fuzzy Sets and Systems 67, pp. 101–117.

    Google Scholar 

  • Hedley, B. (1992): A Fundamental Approach to Strategy Development, (Reprinted from Long Range Planning), in: Hahn, D.; Taylor, B. (eds.): Strategische Unternehmensplanung, 6. ed., Heidelberg, pp. 176–202.

    Google Scholar 

  • Horwitch, M.; Thietart, R.A. (1987): The effect of business interdependencies on product R&D-intensive business performance, in: Management Science 33, No. 2, pp. 178–197.

    Google Scholar 

  • Itakura, H.; Nishikawa, Y. (1984): Fuzzy network technique for technological forecasting, in: Fuzzy Sets and Systems 14, pp. 99–113.

    Google Scholar 

  • Kort, P.M. (1998): Optimal R&D investment of the firm, in: OR Spektrum 20, No. 3, pp. 155–164.

    Google Scholar 

  • Knosala, R.; Pedrycz, W. (1992): Evaluation of design alternatives in mechanical engineering, in: Fuzzy Sets and Systems 47, pp. 269–280.

    Google Scholar 

  • Lasek, M. (1992): Hierarchical structures of fuzzy ratings in the analysis of strategic goals of enterprises, in: Fuzzy Sets and Systems 50, pp. 127–134.

    Google Scholar 

  • Lee, J.; Lee, S.; Bae, Z.-T. (1986): R&D project selection: behavior and practice in a newly industrializing country, in: IEEE Transactions on Engineering Management 33, No. 3, pp. 141–147.

    Google Scholar 

  • Liberatore, M.J. (1987): An extension of the analytic hierarchy process for industrial R&D project selection and resource allocation, in: IEEE Transactions on Engineering Management 34, No. l,pp. 12–18.

    Google Scholar 

  • Liberatore, M.J.; Stylianou, A.C. (1995): Expert support systems for new product development decision making: A modeling framework and applications, in: Management Science 41, No. 8, pp. 1296–1316.

    Google Scholar 

  • Liberatore, M.J.; Titus, G.J. (1983): The practice of management science in R&D project management, in: Management Science 29, No. 8, pp. 962–974.

    Google Scholar 

  • Lockyer, K.; Gordon, J. (1992): Critical Path Analysis and other Project Network Techniques, 5. ed., repr., London.

    Google Scholar 

  • Lootsma, F.A.; Mensch, T.C.A.; Vos, F.A. (1990): Multi-criteria analysis and budget reallocation in long-term research planning, in: European Journal of Operational Research 47, pp. 293–305.

    Google Scholar 

  • Madey, G.R.; Dean, B.V. (1985): Strategic planning for investment in R&D using decision analysis and mathematical programming, in: IEEE Transactions on Engineering Management 32, No. 2, pp. 84–90.

    Google Scholar 

  • McCahon, C.S. (1993): Using PERT as an approximation of fuzzy project-network analysis, in: IEEE Transactions on Engineering Management 40, No. 2, pp. 146–153.

    Google Scholar 

  • Mon, D.-L.; Cheng, C.-H; Lu, H.-C. (1995): Application of fuzzy distributions on project management, in: Fuzzy Sets and Systems 73, pp. 227–234.

    Google Scholar 

  • Onisawa, T.; Sugeno, M.; Nishiwaki, Y.; Kawai, H; Harima, Y. (1986): Fuzzy measure analysis of public attitude towards the use of nuclear energy, in: Fuzzy Sets and Systems 20, pp. 259–289.

    Google Scholar 

  • Pagnoni, A. (1990): Project Engineering, Computer-Oriented Planning and Operational Decision Making, Berlin, Heidelberg.

    MATH  Google Scholar 

  • Pfeiffer, W.; Dögl, R. (1997): Das Technologie-Portfolio-Konzept zur Beherrschung der Schnittstelle Technik und Unternehmensstrategie, in: Hahn, D.; Taylor, B. (eds.): Strategische Unternehmensplanung — strategische Untemehmensfuhrung, 7., rev. ed., Heidelberg, pp. 407–435.

    Google Scholar 

  • Porter, ME. (1980): Competitive Strategy, New York.

    Google Scholar 

  • Porter, M.E. (1985): Competitive Advantage, New York.

    Google Scholar 

  • Rabetge, C. (1991): Fuzzy Sets in der Netzplantechnik, Wiesbaden.

    Book  Google Scholar 

  • Raelin, J.A.; Balachandra, R. (1985): R&D project termination in high-tech industries, in: IEEE Transactions on Engineering Management 32, No. 1, pp. 16–23.

    Google Scholar 

  • Rommelfanger, H.J. (1994): Network analysis and information flow in fuzzy environment, in: Fuzzy Sets and Systems 67, pp. 119–128.

    Google Scholar 

  • Saaty, T.L. (1990): The Analytic Hierarchy Process — Planning, Priority Setting, Resource Allocation, 2nd ed., Pittsburgh, PA 1990.

    Google Scholar 

  • Schmidt, R.L. (1993): A model for R&D project selection with combined benefit, outcome, and resource interactions, in: IEEE Transactions on Engineering Management 40, No. 4, pp. 403–410.

    Google Scholar 

  • Sebastian, H.-J. (1994): Intelligente Entscheidungsunterstützung bei der Systemkonfigurierung, in: Werners, B., Gabriel, R. (Hrsg.): Operations Research, Reflexionen aus Theorie und Praxis, Festschrift zum 60. Geburtstag von Hans-Jürgen Zimmermann, Heidelberg, pp. 275–304.

    Chapter  Google Scholar 

  • Souder, W.E.; Mandakovic, T. (1986): R&D project selection models, in: Research Management 29, pp. 36–42.

    Google Scholar 

  • Steele, L.W. (1988): Selecting R&D programs and objectives, in: Research Technology Management 31, pp. 17–36.

    Google Scholar 

  • Wang, M.-JJ.; Chang, T.-C. (1995): Tool steel materials selection under fuzzy environment, in: Fuzzy Sets and Systems 72, pp. 263–270.

    Google Scholar 

  • Watts, K.M.; Higgins, J.C. (1987): The use of advanced management techniques in R&D, in: OMEGA International Journal of Management Science 15, No. 1, pp. 21–29.

    Google Scholar 

  • Weber, R.; Werners, B.; Zimmermann, H.-J. (1990): Planning models for research and development, in: European Journal of Operational Research 48, pp. 175–188.

    Google Scholar 

  • Werners, B. (1984): Interaktive Entscheidungsunterstützung durch ein flexibles mathematisches Programmierungssystem, München.

    Google Scholar 

  • Werners, B. (1987): Interactive multiple objective programming subject to flexible constraints, in: European Journal of Operational Research 31, pp. 342–349.

    Google Scholar 

  • Werners, B. (1988): Aggregation models in mathematical programming, in: Mitra, G. (ed.): Mathematical Models for Decision Support, Berlin, pp. 295–319.

    Chapter  Google Scholar 

  • Werners, B. (1993): Unterstützung der strategischen Technologieplanung durch wissensbasierte Systeme, Aachener Beiträge zu den Wirtschaftswissenschaften, Aachen.

    Google Scholar 

  • Wood, K.L.; Otto, K.N.; Antonsson, E.K. (1992): Engineering design calculations with fuzzy parameters, in: Fuzzy Sets and Systems 52, pp. 1–20.

    Google Scholar 

  • Zadeh, L.A. (1983): The role of fuzzy logic in the management of uncertainty in expert systems, in: Fuzzy Sets and Systems 11, No. 3, pp. 199–277.

    Google Scholar 

  • Zirnmermann, H.-J. (1978): Fuzzy programming and linear programming with several objective functions, in: Fuzzy Sets and Systems 1, pp. 45–55.

    Google Scholar 

  • Zirnmermann, H.-J. (1987): Fuzzy Sets, Decision Making, and Expert Systems, Boston.

    Book  Google Scholar 

  • Zimmermann, H.-J. (1988): Interactive decision support for semi-structured mathematical programming problems, in: Mitra, G. (ed.): Mathematical Models for Decision Support, Berlin, pp. 307–319.

    Chapter  Google Scholar 

  • Zimmermann, H.-J. (1989): Strategic planning, operations research and knowledge based systems, in: Verdegay, J.-L., Delgado, M. (eds.): The Interface between Artificial Intelligence and Operations Research in Fuzzy Environment, Köln, pp. 253–274.

    Google Scholar 

  • Zimmermami, H.-J. (1996): Fuzzy Set Theory — and Its Applications, 3rd ed., Boston, Dordrecht, London.

    Google Scholar 

  • Zimmermann, H.-J.; Sebastian, H.-J. (1994): Fuzzy design — Integration of fuzzy theory with knowledge-based system-design, in: Proceedings of The Third IEEE Conference on Fuzzy Systems, June 26 - June 29, 1994, Orlando, pp. 352–357.

    Chapter  Google Scholar 

  • Zimmermann, H.-J.; Zysno, P. (1980): Latent connectives in human decision making, in: Fuzzy Sets and Systems 4, pp. 37–51.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer Science+Business Media New York

About this chapter

Cite this chapter

Werners, B., Weber, R. (1999). Decision and Planning in Research and Development. In: Zimmermann, HJ. (eds) Practical Applications of Fuzzy Technologies. The Handbooks of Fuzzy Sets Series, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4601-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-4601-6_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7079-6

  • Online ISBN: 978-1-4615-4601-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Navigation