Multi-objective optimal public investment: An extended model and genetic algorithm-based case study

Lei Tian; Liyan Han; Hai Huang

doi:10.1007/978-3-540-71618-1_35

Multi-objective optimal public investment: An extended model and genetic algorithm-based case study

Lei Tian^*
, Liyan Han
, Hai Huang

^*Corresponding author for this work

School of Economics and Management

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings
Publisher	Springer Verlag
Pages	314-322
Number of pages	9
Edition	PART 1
ISBN (Print)	9783540715894
DOIs	https://doi.org/10.1007/978-3-540-71618-1_35
State	Published - 2007
Event	8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007 - Warsaw, Poland Duration: 11 Apr 2007 → 14 Apr 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4431 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007
Country/Territory	Poland
City	Warsaw
Period	11/04/07 → 14/04/07

Access to Document

10.1007/978-3-540-71618-1_35

Cite this

Tian, L., Han, L., & Huang, H. (2007). Multi-objective optimal public investment: An extended model and genetic algorithm-based case study. In Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings (PART 1 ed., pp. 314-322). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4431 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-71618-1_35

Tian, Lei ; Han, Liyan ; Huang, Hai. / Multi-objective optimal public investment : An extended model and genetic algorithm-based case study. Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 314-322 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{e778ff90858d4b548fd410ac0fec946d,

title = "Multi-objective optimal public investment: An extended model and genetic algorithm-based case study",

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.",

author = "Lei Tian and Liyan Han and Hai Huang",

year = "2007",

doi = "10.1007/978-3-540-71618-1\_35",

language = "英语",

isbn = "9783540715894",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 1",

pages = "314--322",

booktitle = "Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings",

address = "德国",

edition = "PART 1",

note = "8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007 ; Conference date: 11-04-2007 Through 14-04-2007",

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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 Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4431 LNCS, Springer Verlag, pp. 314-322, 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, Warsaw, Poland, 11/04/07. https://doi.org/10.1007/978-3-540-71618-1_35

Multi-objective optimal public investment: An extended model and genetic algorithm-based case study. / Tian, Lei; Han, Liyan; Huang, Hai.
Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 314-322 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4431 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Tian L, Han L, Huang H. Multi-objective optimal public investment: An extended model and genetic algorithm-based case study. In Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 314-322. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-71618-1_35

Multi-objective optimal public investment: An extended model and genetic algorithm-based case study

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