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| Research on Distributed Flexible Flow Shop Scheduling Problem with Loading Efficiency and Load Balancing Constraints |
| Received:May 09, 2024 Revised:June 11, 2024 |
| DOI：10.11981/j.issn.1000-6842.2025.01.169 |
| Key Words:production scheduling;distributed flexible flow shop;constrained optimization problem;NSGA-II |
| Fund Project:国家自然科学基金（52305550）；五邑大学港澳联合研发基金（2022WGALH18）。 |
| Author Name | Affiliation | Postcode | | ZHONG Meisong | School of Electronics and Information Engineering， Wuyi University， Jiangmen， Guangdong Province， 529020 | 529020 | | ZENG Zhiqiang* | School of Electronics and Information Engineering， Wuyi University， Jiangmen， Guangdong Province， 529020 | 529020 |
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| Abstract: |
| With total cost and makespan as optimization objectives， based on the Non-dominated Sorting Genetic Algorithm （NSGA-II） framework， the algorithm was improved by using multi-crossover operation fusion strategy and constraint handling techniques， and a distributed flexible flow shop scheduling model that combines loading efficiency and load balancing constraints was constructed in this study. According to the actual data sourced from a household paper manufacturing enterprise which configured a typical distributed flexible flow shop， several examples of simulation experiments were generated to verify the effectiveness and superiority of the improved algorithm. The results showed that compared with NSGA-II， the production scheduling scheme obtained from improved NSGA-II had an average total cost reduction of about 1.91% and an average makespan reduction of about 4.47%. |
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