Application of Improved Frog Leaping Algorithm in Multi objective Optimization of Engineering Project Management

Yongxian Wang; Junxia Ma; Yanrong Zhang

doi:10.31181/dmame712024896

Authors

Yongxian Wang School of Civil Engineering, Hebei Polytechnic Institute, Shijiazhuang, China https://orcid.org/0000-0003-3997-6791
Junxia Ma School of Civil Engineering, Hebei Polytechnic Institute, Shijiazhuang, China https://orcid.org/0009-0000-9606-4372
Yanrong Zhang Shijiazhuang Construction Group Co., Ltd, Shijiazhuang, China https://orcid.org/0009-0007-3801-0932

DOI:

https://doi.org/10.31181/dmame712024896

Keywords:

SFLA, NSGA-II, Multi objective optimization, Project management

Abstract

The development of information has promoted the development of various industries, and the development of industries will inevitably lead to intensified competition, including the construction industry. To enhance the competitiveness of construction enterprises in the industry, a multi-objective optimization model for construction project management has been proposed. At the same time, carbon emission was included as one of the optimization objectives in the experiment. This can also align the construction industry with the concept of modern green development. A non-dominated sorting genetic algorithm with elite strategy was proposed to improve the hybrid frog leaping algorithm, and the improved hybrid frog leaping algorithm was used to solve multi-objective optimization problems. The improved hybrid frog leaping algorithm performed better in solving multi-objective optimization problems. The improved hybrid frog leaping algorithm found a total of 132 Pareto solution sets, while the non-dominated sorting genetic algorithm with elite strategy only found 23 Pareto solution sets. And the solution set of the improved hybrid frog leaping algorithm is closer to the optimal position. The optimized duration and cost of the improved hybrid frog leaping algorithm are lower, with an optimal duration of 135 days and a minimum cost of $20,000. A multi-objective optimization model for engineering project management incorporating carbon emissions was successfully constructed in the study, and the multi-objective optimization problem was solved.

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