Title: Resources programming model of government investment project group based on improved firefly algorithm

Authors: Yunna Wu; Xinli Xiao; Zongyun Song

Addresses: School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Huilongguan Town, Changping District, Beijing 102206, China ' School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Huilongguan Town, Changping District, Beijing 102206, China ' School of Economics and Management, North China Electric Power University, No. 2 Beinong Road, Huilongguan Town, Changping District, Beijing 102206, China

Abstract: Government investment project group (GIPG) plays an important role in increasing the welfare of the public, so the public is concerned about its investment efficiency, which can be reflected by resource programming level of GIPG. Previous research pays little attention to this field, and several problems exist: ordinary resource programming procedure is directly adopted; project management targets only focus on cost and schedule and the proposed optimisation algorithms are inapplicable. Hence, this research is carried out as follows: first, resource programming procedure of GIPG is organised. Second, the strategic targets of GIPG are determined based on the national, regional planning, and the projects targets are determined based on strategic targets, which ensure the coherence of national planning and projects targets. Third, the newly proposed optimisation algorithm-Gaussian firefly algorithm (GFA) is described and its effectiveness is validated through comparison with other algorithms. Finally, a case study demonstrates the effectiveness of resource programming method of GIPG.

Keywords: AOPG; administration office of project group; EC; expert committee; FA; firefly algorithm; GA; genetic algorithm; GDA; Gaussian disturbance algorithm; GFA; Gaussian firefly algorithm; GIP; government investment project; GIPG; government investment project group; PSO; particle swarm optimisation; resource programming model.

DOI: 10.1504/IJTPM.2017.084536

International Journal of Technology, Policy and Management, 2017 Vol.17 No.2, pp.123 - 138

Received: 25 Jul 2016
Accepted: 03 Sep 2016
Published online: 13 Jun 2017 *

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