THE SOLUTION TO THE PROJECT SCHEDULING PROBLEM BY USING AN IMPROVED GENETIC ALGORITHM

Nowadays, managing and allocating resources for projects has become increasingly essential for managers. A critical factor affecting the success of a project is the work assignment plan for workers to optimize the completion time. Current solutions to project scheduling problems have not been thoroughly addressed; thus, in this study, we model the labor assignment process in project production as a scheduling problem. To solve this problem, we use an improved genetic algorithm named GA-RT (Genetic Algorithm with Random Crossover and Negative Tournament Selection) and conduct experiments on the iMOPSE standard dataset. Experimental results show that the proposed GA-RT algorithm can effectively solve the project scheduling problem, achieving better performance compared to existing algorithms.

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Publication Details

Journal
Journal of Science Natural Science
Published
2024-10-31
DOI
https://doi.org/10.18173/2354-1059.2024-0035
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00

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article

THE SOLUTION TO THE PROJECT SCHEDULING PROBLEM BY USING AN IMPROVED GENETIC ALGORITHM

Huu Dang Quoc, Loc Nguyen The, Trần Thanh Thiên Trúc, Do Ba Chin
Journal of Science Natural Science
BIM and Construction Integration
article

THE SOLUTION TO THE PROJECT SCHEDULING PROBLEM BY USING AN IMPROVED GENETIC ALGORITHM

Huu Dang Quoc, Loc Nguyen The, Trần Thanh Thiên Trúc, Do Ba Chin
article en

Abstract

Nowadays, managing and allocating resources for projects has become increasingly essential for managers. A critical factor affecting the success of a project is the work assignment plan for workers to optimize the completion time. Current solutions to project scheduling problems have not been thoroughly addressed; thus, in this study, we model the labor assignment process in project production as a scheduling problem. To solve this problem, we use an improved genetic algorithm named GA-RT (Genetic Algorithm with Random Crossover and Negative Tournament Selection) and conduct experiments on the iMOPSE standard dataset. Experimental results show that the proposed GA-RT algorithm can effectively solve the project scheduling problem, achieving better performance compared to existing algorithms.

Journal of Science Natural Science
Hanoi National University of Education (VN), Thuongmai University (VN), VNU University of Science (VN)
Bộ Giáo dục và Ðào tạo, Đại học Quốc gia Hà Nội
Openalex Percentile: Top 76%
BIM and Construction Integration
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THE SOLUTION TO THE PROJECT SCHEDULING PROBLEM BY USING AN IMPROVED GENETIC ALGORITHM — Huu Dang Quoc, Loc Nguyen The, et al. · Journal of Science Natural Science (2024) | TGRS Research Map | TGRS