An adaptive scheduling framework for dynamic scheduling problem with random job arrivals and cancellations DOI

Yixun Zhao,

Haidan Wang,

Rutong Zhang

и другие.

Опубликована: Апрель 12, 2024

Язык: Английский

Improved lion swarm optimization algorithm to solve the multi-objective rescheduling of hybrid flowshop with limited buffer DOI Creative Commons

Tingyu Guan,

Tingxin Wen,

Bencong Kou

и другие.

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2024, Номер 36(5), С. 102077 - 102077

Опубликована: Май 29, 2024

As the realities of production and operation in green intelligent workshops become more variable, adverse risks arising from disruptions to modernized workshop energy consumption schedules customer churn caused by dynamic events are increasing. In order solve those problems, we take hybrid flow shop as research subject, use buffer capacity automated guided vehicles (AGVs) transport devices resource constraints, construct a multi-objective rescheduling model that considers both satisfaction. According characteristics, an improved lion swarm optimization algorithm (ILSO) is designed above model. To improve initial solution quality global search capability algorithm, ILSO combining reverse learning initialization strategy Logistic chaotic mapping with tabu strategy. The results experiments on proposed different sizes arithmetic cases real indicate can effectively bi-objective problem oriented inserting orders, provide scheduling solutions for manufacturing enterprises achieve purpose transformation manufacturing.

Язык: Английский

Процитировано

2
Multi-population coevolutionary algorithm for a green multi-objective flexible job shop scheduling problem with automated guided vehicles and variable processing speed constraints DOI
Chao Liu, Yuyan Han, Yuting Wang

и другие.

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 91, С. 101774 - 101774

Опубликована: Ноя. 15, 2024

Язык: Английский

Процитировано

2
Mixed-production flexible assembly job shop scheduling considering parallel assembly sequence variations under dual-resource constraints using multi-objective hybrid memetic algorithm DOI
Xin Lu, Cong Lu

Computers & Operations Research, Год журнала: 2024, Номер unknown, С. 106932 - 106932

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2
A crew task allocation and sequencing method considering workload distribution and minimum task completion time DOI
Jianhua Sun,

Suihuai Yu,

Jianjie Chu

и другие.

Kybernetes, Год журнала: 2024, Номер unknown

Опубликована: Июнь 1, 2024

Purpose In situations where the crew is reduced, optimization of task allocation and sequencing (CTAS) can significantly enhance operational efficiency man-machine system by rationally distributing workload minimizing completion time. Existing related studies exhibit a limited consideration distribution involve violation precedence constraints in solution process. This study proposes CTAS method to address these issues. Design/methodology/approach The defines visual, auditory, cognitive psychomotor (VACP) load balancing objectives integrates them with minimum time ensure equitable execution efficiency, then multi-objective model for constructed. Subsequently, it designs population initialization strategy repair mechanism maintain sequence feasibility, utilizes improve non-dominated sorting genetic algorithm III (NSGA-III) solving model. Findings validated through numerical example involving mission specific type armored vehicle. results demonstrate that achieves integrating VACP balancing. Moreover, improved NSGA-III maintains feasibility thus reduces computation Originality/value achieve search optimal scheme. It provides novel perspective planners objective determination methodologies CTAS.

Язык: Английский

Процитировано

1
An adaptive scheduling framework for dynamic scheduling problem with random job arrivals and cancellations DOI

Yixun Zhao,

Haidan Wang,

Rutong Zhang

и другие.

Опубликована: Апрель 12, 2024

Язык: Английский

Процитировано

0