A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation
The permutation flowshop problem is a classic machine scheduling problem where n jobs
must be processed on a set of m machines disposed in series and where each job must visit …
must be processed on a set of m machines disposed in series and where each job must visit …
[HTML][HTML] Neural agent-based production planning and control: An architectural review
Nowadays, production planning and control must cope with mass customization, increased
fluctuations in demand, and high competition pressures. Despite prevailing market risks …
fluctuations in demand, and high competition pressures. Despite prevailing market risks …
Process characterisation of 3D-printed FDM components using improved evolutionary computational approach
Fused deposition modelling (FDM) is an additive manufacturing technique deployed to
fabricate the functional components leading to shorter product development times with less …
fabricate the functional components leading to shorter product development times with less …
Hybrid Deep Neural Network Scheduler for Job‐Shop Problem Based on Convolution Two‐Dimensional Transformation
In this paper, a hybrid deep neural network scheduler (HDNNS) is proposed to solve job‐
shop scheduling problems (JSSPs). In order to mine the state information of schedule …
shop scheduling problems (JSSPs). In order to mine the state information of schedule …
Real-time neural network scheduling of emergency medical mask production during COVID-19
During the outbreak of the novel coronavirus pneumonia (COVID-19), there is a huge
demand for medical masks. A mask manufacturer often receives a large amount of orders …
demand for medical masks. A mask manufacturer often receives a large amount of orders …
An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes
Soil nailing is one of the slope stabilisation techniques useful for the strengthening of
existing slopes. It helps to reinforce the soil with passive inclusions that increase the overall …
existing slopes. It helps to reinforce the soil with passive inclusions that increase the overall …
A multi-gene genetic programming model for estimating stress-dependent soil water retention curves
Soil water retention curve (SWRC) is an important parameter required for seepage
modelling in unsaturated soil and is used for analysing rainfall-induced slope failures …
modelling in unsaturated soil and is used for analysing rainfall-induced slope failures …
Flowshop scheduling with artificial neural networks
For effective modelling of flowshop scheduling problems, artificial neural networks (ANNs),
due to their robustness, parallelism and predictive ability have been successfully used by …
due to their robustness, parallelism and predictive ability have been successfully used by …
Preliminary discussion regarding SVM kernel function selection in the twofold rock slope prediction model
Y Zhang, M Dai, Z Ju - Journal of Computing in Civil Engineering, 2016 - ascelibrary.org
The kernel function, which is an important component of support vector machine (SVM)
theory, directly affects the results of a prediction model. When establishing an effective …
theory, directly affects the results of a prediction model. When establishing an effective …
Neural network based modeling and optimization of deep drawing–extrusion combined process
A combined deep drawing–extrusion process is modeled with artificial neural networks
(ANN's). The process is used for manufacturing synchronizer rings and it combines sheet …
(ANN's). The process is used for manufacturing synchronizer rings and it combines sheet …