A genetic algorithm-based double-objective multi-constraint optimal cross-region cross-sector public investment model

Authors:
Tian Lei;Liu Lieli;Han Liyan;Huang Hai
Affiliations:
School of Economics and Management, Beihang University, Beijing, P.R. China;School of Economics and Management, Beihang University, Beijing, P.R. China;School of Economics and Management, Beihang University, Beijing, P.R. China;School of Computer Science and Engineering, Beihang University, Beijing, P.R. China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

Citing 1
Cited 1

Genetic Algorithms

Genetic Algorithms

Multi-objective Optimal Public Investment: An Extended Model and Genetic Algorithm-Based Case Study

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I

Quantified Score

Hi-index	0.00

Visualization

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.