Flexible job shop scheduling problem under Industry 5.0: A survey on human reintegration, environmental consideration and resilience improvement

C Destouet, H Tlahig, B Bettayeb, B Mazari - Journal of Manufacturing …, 2023 - Elsevier
Abstract The Job Shop Scheduling Problem (JSSP) has been widely studied in recent
decades. Various approaches have been proposed to support scheduling decisions …

The evolution of production scheduling from Industry 3.0 through Industry 4.0

Z Jiang, S Yuan, J Ma, Q Wang - International Journal of …, 2022 - Taylor & Francis
Since the Third Industrial Revolution, technology and the global economy have developed
rapidly. Driven by market demand and the development of science and technology, the …

Proposed managerial competencies for Industry 4.0–Implications for social sustainability

SV Shet, V Pereira - Technological Forecasting and Social Change, 2021 - Elsevier
Abstract Industry 4.0 (I4. 0) is creating a paradigm shift within the current industrial context.
The study presented in this paper involved identifying and proposing the managerial …

Surrogate-assisted evolutionary multitask genetic programming for dynamic flexible job shop scheduling

F Zhang, Y Mei, S Nguyen, M Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Dynamic flexible job shop scheduling (JSS) is an important combinatorial optimization
problem with complex routing and sequencing decisions under dynamic environments …

Real-time production scheduling in the Industry-4.0 context: Addressing uncertainties in job arrivals and machine breakdowns

M Ghaleb, H Zolfagharinia, S Taghipour - Computers & Operations …, 2020 - Elsevier
The utilization of real-time information in production scheduling decisions becomes possible
with the help of new developments in Information Technology and Industrial Informatics …

Multitask genetic programming-based generative hyperheuristics: A case study in dynamic scheduling

F Zhang, Y Mei, S Nguyen, KC Tan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Evolutionary multitask learning has achieved great success due to its ability to handle
multiple tasks simultaneously. However, it is rarely used in the hyperheuristic domain, which …

Literature review on using data mining in production planning and scheduling within the context of cyber physical systems

PM Seeger, Z Yahouni, G Alpan - Journal of Industrial Information …, 2022 - Elsevier
Within the context of Industry 4.0, Cyber Physical Systems (CPS) are defined as
technologies that can manage interconnected systems between its physical assets and …

Production planning and scheduling in Cyber-Physical Production Systems: a review

DA Rossit, F Tohme, M Frutos - International journal of computer …, 2019 - Taylor & Francis
The study of scheduling procedures has generated important contributions to the
improvement of productivity in different industrial branches. In recent years, the incorporation …

On reliability of reinforcement learning based production scheduling systems: a comparative survey

C Waubert de Puiseau, R Meyes, T Meisen - Journal of Intelligent …, 2022 - Springer
The deep reinforcement learning (DRL) community has published remarkable results on
complex strategic planning problems, most famously in virtual scenarios for board and video …

Scheduling under uncertainty for Industry 4.0 and 5.0

K Bakon, T Holczinger, Z Süle, S Jaskó… - IEEE Access, 2022 - ieeexplore.ieee.org
This article provides a review about how uncertainties in increasingly complex production
and supply chains should be addressed in scheduling tasks. Uncertainty management will …