Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints

With the transformation of manufacturing towards intelligence and flexibility, the workshop scheduling problem, as a typical combinatorial optimization problem, is facing increasingly complex constraints and requirements. In the actual production process, order constraints and assembly constraints o...

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書誌詳細
出版年:IEEE Access
第一著者: Tingting Qu
フォーマット: 論文
言語:英語
出版事項: IEEE 2025-01-01
主題:
オンライン・アクセス:https://ieeexplore.ieee.org/document/11005464/
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author Tingting Qu
author_facet Tingting Qu
author_sort Tingting Qu
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container_title IEEE Access
description With the transformation of manufacturing towards intelligence and flexibility, the workshop scheduling problem, as a typical combinatorial optimization problem, is facing increasingly complex constraints and requirements. In the actual production process, order constraints and assembly constraints often significantly affect production efficiency and scheduling effectiveness. The traditional centralized scheduling method is no longer able to meet the requirements for flexibility, real-time performance, and efficiency in modern manufacturing environments. To solve this problem, a distributed workshop scheduling model based on order constraints and assembly constraints is proposed, aiming to improve the scheduling efficiency of the workshop under complex constraint conditions. For this model, an improved greedy algorithm was combined to solve it, and particle swarm optimization algorithm was introduced to enhance the local and global search capabilities of the distributed scheduling system, effectively addressing the computational complexity in large-scale production environments. The experimental results show that the research model performs well in optimizing scheduling, with a maximum completion time of 40.49 hours, an average processing waiting time of 1.46 hours, and a resource utilization rate of over 95%. These results indicate that the proposed solution algorithm can significantly shorten the production cycle, improve resource utilization, and have high real-time scheduling capabilities, making it particularly suitable for solving workshop scheduling problems with complex orders and assembly constraints.
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spelling doaj-art-e3ba094c8f8c49b29adc3fede28830c82025-08-20T03:13:43ZengIEEEIEEE Access2169-35362025-01-0113882008821410.1109/ACCESS.2025.357036211005464Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly ConstraintsTingting Qu0https://orcid.org/0009-0005-1513-8461School of Mathematics and Big Data, Chongqing University of Education, Chongqing, ChinaWith the transformation of manufacturing towards intelligence and flexibility, the workshop scheduling problem, as a typical combinatorial optimization problem, is facing increasingly complex constraints and requirements. In the actual production process, order constraints and assembly constraints often significantly affect production efficiency and scheduling effectiveness. The traditional centralized scheduling method is no longer able to meet the requirements for flexibility, real-time performance, and efficiency in modern manufacturing environments. To solve this problem, a distributed workshop scheduling model based on order constraints and assembly constraints is proposed, aiming to improve the scheduling efficiency of the workshop under complex constraint conditions. For this model, an improved greedy algorithm was combined to solve it, and particle swarm optimization algorithm was introduced to enhance the local and global search capabilities of the distributed scheduling system, effectively addressing the computational complexity in large-scale production environments. The experimental results show that the research model performs well in optimizing scheduling, with a maximum completion time of 40.49 hours, an average processing waiting time of 1.46 hours, and a resource utilization rate of over 95%. These results indicate that the proposed solution algorithm can significantly shorten the production cycle, improve resource utilization, and have high real-time scheduling capabilities, making it particularly suitable for solving workshop scheduling problems with complex orders and assembly constraints.https://ieeexplore.ieee.org/document/11005464/Order constraintsassembly constraintsworkshop schedulinggreedy algorithmdistributed scheduling
spellingShingle Tingting Qu
Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
Order constraints
assembly constraints
workshop scheduling
greedy algorithm
distributed scheduling
title Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
title_full Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
title_fullStr Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
title_full_unstemmed Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
title_short Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints
title_sort algorithm for solving distributed workshop scheduling model based on order constraints and assembly constraints
topic Order constraints
assembly constraints
workshop scheduling
greedy algorithm
distributed scheduling
url https://ieeexplore.ieee.org/document/11005464/
work_keys_str_mv AT tingtingqu algorithmforsolvingdistributedworkshopschedulingmodelbasedonorderconstraintsandassemblyconstraints