Skip to main content
SpringerLink
Log in

Introduction

  • Chapter
  • First Online:
Fuzzy Hierarchical Model for Risk Assessment

  • 1583 Accesses

Abstract

Making decisions is part of human life. Nevertheless, making a good decision is not always easy. This is mainly because there are many contributing factors (i.e. we have multiple criteria) in a problem. Even worse, many of them involve multiple objectives (i.e. multiple input, multiple output). That means the objectives of the problems in question may be conflicting with each other. On the one hand, solving such problems can entertain multiple dimensionalities.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

References

  • Buckley, J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17, 233–247.

    Article  MathSciNet  MATH  Google Scholar 

  • Chan, F. T. S., & Chan, H. K. (2004). A comprehensive survey and future trend of simulation study on FMS scheduling. Journal of Intelligent Manufacturing, 15(1), 87–102.

    Article  Google Scholar 

  • Chan, H. K., & Chan, F. T. S. (2010). Comparative study of adaptability and flexibility in distributed manufacturing supply chains. Decision Support Systems, 48(2), 331–341.

    Article  Google Scholar 

  • Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655.

    Article  MATH  Google Scholar 

  • Chen, S. J., & Chen, S. M. (2003). Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. IEEE Transactions on Fuzzy Systems, 11(1), 45–56.

    Article  Google Scholar 

  • Gómez-Limón, J. A., Arriaza, M., & Riesgo, L. (2003). An MCDM analysis of agricultural risk aversion. European Journal of Operational Research, 151(3), 569–585.

    Article  MathSciNet  MATH  Google Scholar 

  • Hwang, C. L., & Yoon, K. (1981). Multiple attributes decision making methods and applications. Berlin: Springer.

    Book  Google Scholar 

  • Khadam, I. M., & Kaluarachchi, J. J. (2003). Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water. Environmental Impact Assessment Review, 23(6), 683–721.

    Article  Google Scholar 

  • Krohling, R. A., & De Souza, T. T. M. (2012). Combining prospect theory and fuzzy numbers to multi-criteria decision making. Expert Systems with Applications, 39(13), 11487–11493.

    Article  Google Scholar 

  • Nieto-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assessment. International Journal of Project Management, 29(2), 220–231.

    Article  Google Scholar 

  • Saaty, T. L. (1978). Modeling unstructured decision problems—the theory of analytical hierarchies. Mathematics and Computers in Simulation, 20(3), 147–158.

    Article  MATH  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

    MATH  Google Scholar 

  • Saaty, T. L., & Takizawa, M. (1986). Dependence and independence: From linear hierarchies to nonlinear networks. European Journal of Operational Research, 26, 229–237.

    Article  MathSciNet  MATH  Google Scholar 

  • Wang, X., Chan, H. K., Yee, R. W. Y., & Diaz-Rainey, I. (2012). A two-stage fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain. International Journal of Production Economics, 135(2), 595–606.

    Article  Google Scholar 

  • Wang, X., Li, D., O’Brien, C., & Li, Y. (2010). A production planning model to reduce risk and improve operations management. International Journal of Production Economics, 124(2), 463–474.

    Article  Google Scholar 

  • Wieland, A., & Wallenburg, C. M. (2012). Dealing with supply chain risks: Linking risk management practices and strategies to performance. International Journal of Physical Distribution and Logistics Management, 42(10), 887–905.

    Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  MathSciNet  MATH  Google Scholar 

  • Zafra-Cabeza, A., Ridao, M. A., Camacho, E. F., Kempf, K. G., & Rivera, D. E. (2007). Managing risk in semiconductor manufacturing: A stochastic predictive control approach. Control Engineering Practice, 15(8), 969–984.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Norwich Business School, University of East Anglia, Norwich, NR4 7TJ, UK

    Hing Kai Chan

  2. Department of Management, University of Bristol, Bristol, BS8 1TN, UK

    Xiaojun Wang

Authors
  1. Hing Kai Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaojun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hing Kai Chan .

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Chan, H.K., Wang, X. (2013). Introduction. In: Fuzzy Hierarchical Model for Risk Assessment. Springer, London. https://doi.org/10.1007/978-1-4471-5043-5_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5043-5_1

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5042-8

  • Online ISBN: 978-1-4471-5043-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation