Abstract
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.
This paper is supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20050006025).
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Lei, T., Lieli, L., Liyan, H., Hai, H. (2006). A Genetic Algorithm-Based Double-Objective Multi-constraint Optimal Cross-Region Cross-Sector Public Investment Model. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_58
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DOI: https://doi.org/10.1007/11881223_58
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