Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II
The traditional construction industry is characterized by high energy consumption and significant carbon emissions, primarily due to its reliance on on-site manual labor and wet operations, which are not only low in mechanization but also result in low material efficiency and substantial constructio...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/15/5/742 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850226169551519744 |
|---|---|
| author | Yishi Zhao Shaokang Du Ming Tu Haichuan Ma Jianga Shang Xiuqiao Xiang |
| author_facet | Yishi Zhao Shaokang Du Ming Tu Haichuan Ma Jianga Shang Xiuqiao Xiang |
| author_sort | Yishi Zhao |
| collection | DOAJ |
| description | The traditional construction industry is characterized by high energy consumption and significant carbon emissions, primarily due to its reliance on on-site manual labor and wet operations, which are not only low in mechanization but also result in low material efficiency and substantial construction waste. Prefabricated construction offers a new solution with its efficient production methods, significantly enhancing material utilization and construction efficiency. This paper focuses on the production scheduling optimization of prefabricated components. The production scheduling directly affects the construction speed and cost of prefabricated buildings. Given the complex modeling and numerous constraints faced by the production of prefabricated components, we propose an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. The algorithm incorporates adaptive operators and greedy concepts for local search, enhancing solution exploration and diversity. We segment the production of prefabricated components into six stages, analyzing dependencies and constraints, and form a comprehensive scheduling model with objectives of minimizing contract penalties, storage costs, and production time. Extensive experiments demonstrate that the improved NSGA-II provides a more balanced and larger set of solutions compared to baseline algorithms, offering manufacturers a wider range of options. This research contributes to the optimization of production scheduling in the prefabricated construction industry, supporting coordinated, sustainable, automated, and transparent production environments. |
| format | Article |
| id | doaj-art-6381faee67ea44a1baa559d3aa79297d |
| institution | OA Journals |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj-art-6381faee67ea44a1baa559d3aa79297d2025-08-20T02:05:09ZengMDPI AGBuildings2075-53092025-02-0115574210.3390/buildings15050742Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm IIYishi Zhao0Shaokang Du1Ming Tu2Haichuan Ma3Jianga Shang4Xiuqiao Xiang5School of Computer Science, China University of Geosciences, Wuhan 430074, ChinaSchool of Computer Science, China University of Geosciences, Wuhan 430074, ChinaIntelligent Construction System Research Institute, China Construction Third Engineering Buerau Group, Wuhan 430075, ChinaSchool of Computer Science, China University of Geosciences, Wuhan 430074, ChinaSchool of Computer Science, China University of Geosciences, Wuhan 430074, ChinaSchool of Computer Science, China University of Geosciences, Wuhan 430074, ChinaThe traditional construction industry is characterized by high energy consumption and significant carbon emissions, primarily due to its reliance on on-site manual labor and wet operations, which are not only low in mechanization but also result in low material efficiency and substantial construction waste. Prefabricated construction offers a new solution with its efficient production methods, significantly enhancing material utilization and construction efficiency. This paper focuses on the production scheduling optimization of prefabricated components. The production scheduling directly affects the construction speed and cost of prefabricated buildings. Given the complex modeling and numerous constraints faced by the production of prefabricated components, we propose an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. The algorithm incorporates adaptive operators and greedy concepts for local search, enhancing solution exploration and diversity. We segment the production of prefabricated components into six stages, analyzing dependencies and constraints, and form a comprehensive scheduling model with objectives of minimizing contract penalties, storage costs, and production time. Extensive experiments demonstrate that the improved NSGA-II provides a more balanced and larger set of solutions compared to baseline algorithms, offering manufacturers a wider range of options. This research contributes to the optimization of production scheduling in the prefabricated construction industry, supporting coordinated, sustainable, automated, and transparent production environments.https://www.mdpi.com/2075-5309/15/5/742offsite manufacturingprefabricated componentscheduling modelmulti-objective optimization algorithm |
| spellingShingle | Yishi Zhao Shaokang Du Ming Tu Haichuan Ma Jianga Shang Xiuqiao Xiang Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II Buildings offsite manufacturing prefabricated component scheduling model multi-objective optimization algorithm |
| title | Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II |
| title_full | Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II |
| title_fullStr | Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II |
| title_full_unstemmed | Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II |
| title_short | Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II |
| title_sort | multi objective scheduling optimization of prefabricated components production using improved non dominated sorting generic algorithm ii |
| topic | offsite manufacturing prefabricated component scheduling model multi-objective optimization algorithm |
| url | https://www.mdpi.com/2075-5309/15/5/742 |
| work_keys_str_mv | AT yishizhao multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii AT shaokangdu multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii AT mingtu multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii AT haichuanma multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii AT jiangashang multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii AT xiuqiaoxiang multiobjectiveschedulingoptimizationofprefabricatedcomponentsproductionusingimprovednondominatedsortinggenericalgorithmii |