知识和数据协同驱动的群体智能决策方法研究综述
蒲志强， 易建强， 刘振， 丘腾海， 孙金林， 李非墨 - 自动化学报, 2022 - aas.net.cn
群体智能(Collectire intelligence, CI) 系统具有广泛的应用前景. 当前的群体智能决策方法主要
包括知识驱动, 数据驱动两大类, 但各自存在优缺点. 本文指出, 知识与数据协同驱动将为群体 …
包括知识驱动, 数据驱动两大类, 但各自存在优缺点. 本文指出, 知识与数据协同驱动将为群体 …
Logistics service scheduling with manufacturing provider selection in cloud manufacturing
In service-oriented manufacturing models, manufacturing resources in different enterprises
are integrated and shared through network, cloud platforms, and logistics. On cloud …
are integrated and shared through network, cloud platforms, and logistics. On cloud …
Inverse model and adaptive neighborhood search based cooperative optimizer for energy-efficient distributed flexible job shop scheduling
Solving the energy-efficient distributed flexible job shop scheduling problem (EEDFJSP)
obtains increased attention. However, most previous studies barely considered the large …
obtains increased attention. However, most previous studies barely considered the large …
A cooperative evolutionary algorithm with simulated annealing for integrated scheduling of distributed flexible job shops and distribution
Production and distribution are two essential parts in supply chains. An integration of
production and distribution has received amount of attention from both academia and …
production and distribution has received amount of attention from both academia and …
Metaheuristics to solve grouping problems: A review and a case study
O Ramos-Figueroa, M Quiroz-Castellanos… - Swarm and Evolutionary …, 2020 - Elsevier
Grouping problems are a special type of combinatorial optimization problems that have
gained great relevance because of their numerous real-world applications. The solution …
gained great relevance because of their numerous real-world applications. The solution …
A hybrid evolutionary algorithm using two solution representations for hybrid flow-shop scheduling problem
As an extension of the classical flow-shop scheduling problem, the hybrid flow-shop
scheduling problem (HFSP) widely exists in large-scale industrial production systems and …
scheduling problem (HFSP) widely exists in large-scale industrial production systems and …
Bi-objective modeling and optimization for stochastic two-stage open shop scheduling problems in the sharing economy
Y Fu, H Li, M Huang, H Xiao - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Nowadays, many manufacturing and service industries prefer to share resources such as
facilities and workers to cooperatively perform tasks, which can efficiently improve resource …
facilities and workers to cooperatively perform tasks, which can efficiently improve resource …
Learning-based grey wolf optimizer for stochastic flexible job shop scheduling
C Lin, Z Cao, MC Zhou - IEEE Transactions on Automation …, 2022 - ieeexplore.ieee.org
This work considers a stochastic flexible job shop scheduling with limited extra resources
and machine-dependent setup time in a semiconductor manufacturing environment, which …
and machine-dependent setup time in a semiconductor manufacturing environment, which …
An improved genetic algorithm with an overlapping strategy for solving a combination of order batching and flexible job shop scheduling problem
Z Liu, J Zha, J Yan, Y Zhang, T Zhao, Q Cheng… - … Applications of Artificial …, 2024 - Elsevier
The problem of flexible job shop batch scheduling represents an extension of the flexible
manufacturing problem. Different batching strategy significantly affects the effect of …
manufacturing problem. Different batching strategy significantly affects the effect of …
A shuffled cellular evolutionary grey wolf optimizer for flexible job shop scheduling problem with tree-structure job precedence constraints
Z Zhu, X Zhou, D Cao, M Li - Applied Soft Computing, 2022 - Elsevier
Along with the growing demands for customized products and small batch production, the
flexible job shop manufacturing environment becomes increasingly popular. Efficient flexible …
flexible job shop manufacturing environment becomes increasingly popular. Efficient flexible …