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Multi-objective Optimal Strategy for Individual Consumption-Investment with Fuzzy Coefficients

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Intelligent Computing (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

The goal of this paper is to solve an optimal consumption-investment problem with fuzzy financial coefficients. A multi-objective fuzzy decision-making model for consumption-investment problem is proposed, based on the uncertainty in some economic factors, to maximize the consumption utility and to maximize the total profit in investment and to minimize the risk in investment. The fuzzy optimal consumption-investment strategy is characterized by maximizing the satisfactory grade of the decision-maker. Finally an effective algorithm is proposed to solve the problem and a numerical example shows the effectiveness and feasibility of this method.

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Author information

Authors and Affiliations

  1. School of Business, Renmin University of China, Beijing, China

    Jie Su

  2. School of Math. and Sys. Sci., Shandong University, Jinan, China

    Jie Su

  3. Department of Mathematics, Southeast University, Nanjing, China

    Xiucui Guan

Authors
  1. Jie Su
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  2. Xiucui Guan
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    De-Shuang Huang

  2. Carnegie Mellon University,  

    Kang Li

  3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Stranmillis Road, BT9 5AH, Belfast, UK

    George William Irwin

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© 2006 Springer-Verlag Berlin Heidelberg

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Su, J., Guan, X. (2006). Multi-objective Optimal Strategy for Individual Consumption-Investment with Fuzzy Coefficients. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_111

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  • DOI: https://doi.org/10.1007/11816157_111

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37271-4

  • Online ISBN: 978-3-540-37273-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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