A Genetic Algorithm-Based Double-Objective Multi-constraint Optimal Cross-Region Cross-Sector Public Investment Model

  • Tian Lei
  • Liu Lieli
  • Han Liyan
  • Huang Hai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)


An optimal public investment model with two objective functions considering efficiency & equity and several constraints such as taxes and capital transfer loss are established by dividing public & private sectors and relaxing several original hypotheses respectively. And the objective functions and constraints are handled to adapt the model into the double-objective multi-constraint programming model suitable for genetic algorithm-based solution. Then encoding and decoding approaches are designed. Finally a case study is carried out to validate the proposed model and the GA-based solution.


Public Investment Optimal Objective Function Simple Labor Capital Transfer Aggregative Production Function 
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  1. 1.
    Gaube, T.: Public Investment and Income Taxation: Redistribution vs. Productive Performance. Journal of Economics 86, 1–18 (2005)MATHCrossRefGoogle Scholar
  2. 2.
    Basu, P., Bandyopadhyay, D.: What Drives the Cross-country Growth and Inequality Correlation. Canadian Journal of Economics 38(4), 1272–1297 (2005)CrossRefGoogle Scholar
  3. 3.
    Brecher, R.A., Chen, Z.Q., Choudhri, E.U.: Dynamic Stability in a Two-country Model of Optimal Growth and International Trade. Journal of Economic Dynamics & Control 29, 583–594 (2005)MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Van, C.L., Vailakis, Y.: Recursive utility and optimal growth with bounded or unbounded returns. Journal of Economic Theory 123, 187–209 (2005)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Jouini, E., Napp, C.: Convergence of Utility Functions and Convergence of Optimal Strategies. Finance and Stochastics (8), 133–144 (2004)Google Scholar
  6. 6.
    Aurell, E., Muratore-Ginanneschi, P.: Growth-Optimal Strategies with Quadratic Friction over Finite-Time Investment Horizons. International Journal of Theoretical and Applied Finance 7(5), 645–657 (2004)MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Saglam, H.C.: Optimal Growth Models and the Lagrange Multiplier. Journal of Mathematical Economics 40, 393–410 (2004)MATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Gómez, M.A.: Optimal Fiscal Policy in the Uzawa-Lucas Model with Externalities. Economic Theory (22), 917–925 (2003)Google Scholar
  9. 9.
    Wu, J.H.: Optimal Regional Growth and Public Investment Models: Theory and Application to the Efficiency-Equity Issue in Taiwan. PQDD doctoral dissertation, Dissertation Abstracts International, Section A, vol. 48(04), p. 1035 (1987)Google Scholar
  10. 10.
    Ramsey, F.: A mathematical theory of saving. Economic Journal 38, 543–559 (1928)CrossRefGoogle Scholar
  11. 11.
    Romer, D.: Advanced Macroeconomics, 2nd edn. McGraw-Hill Co., Inc., New York (2000)Google Scholar
  12. 12.
    Gen, M., Cheng, R.W.: Genetic Algorithms and Engineering Optimization. John Wiley & Sons, Inc., Chichester (2000)Google Scholar
  13. 13.
    Pan, Y., Yu, Z.W., Liu, K.J., Dou, W.: A New Multi-Objective Programming Model of QoS-based Multicast Routing Problem. Computer Engineering and Application (19), C155–C157 (2003)Google Scholar
  14. 14.
    Guo, H.Y., Zhang, L., Jiang, J.: Two-Stage Structural Damage Detection Method with Genetic Algorithms. Journal of Xi’an Jiaotong University 39(5), 485–489 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tian Lei
    • 1
  • Liu Lieli
    • 1
  • Han Liyan
    • 1
  • Huang Hai
    • 2
  1. 1.School of Economics and ManagementBeihang UniversityBeijingP.R. China
  2. 2.School of Computer Science and EngineeringBeihang UniversityBeijingP.R. China

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