Abstract
Under the multi-region and multi-sector consideration, the previous double-objective optimal public investment model is extended to involve optimal employment rate objective and time-flow total income maximization objective first. Then genetic algorithm is applied to solve the multi-objective model. Finally a case study is carried out to verify the superiority of the genetic algorithm-based solution to traditional public investment distribution approach.
This paper is supported by the Innovation Foundation of BUAA for PhD Graduates and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20050006025).
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Tian, L., Han, L., Huang, H. (2007). Multi-objective Optimal Public Investment: An Extended Model and Genetic Algorithm-Based Case Study. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71618-1_35
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DOI: https://doi.org/10.1007/978-3-540-71618-1_35
Publisher Name: Springer, Berlin, Heidelberg
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