Precast production scheduling in off-site construction: Mainstream contents and optimization perspective

L Wang, Y Zhao, X Yin - Journal of Cleaner Production, 2023 - Elsevier
Precast production scheduling (PPS) is a key factor that enables efficient off-site construction
(OSC) and has received considerable attention from researchers. However, there is still a …

A new approach for optimal chiller loading using an improved imperialist competitive algorithm

J Cai, H Yang, T Lai, K Xu - Energy and Buildings, 2023 - Elsevier
A new optimization algorithm based on an improved imperialist competitive algorithm (ICA-
DE) is proposed to reduce the energy consumption of a multi-chiller system. The …

A Q-learning-based hyper-heuristic evolutionary algorithm for the distributed flexible job-shop scheduling problem with crane transportation

ZQ Zhang, FC Wu, B Qian, R Hu, L Wang… - Expert Systems with …, 2023 - Elsevier
With the globalization and sustainable development of the modern manufacturing industry,
distributed manufacturing and scheduling systems that consider environmental effects have …

Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation

J Li, Y Han, K Gao, X Xiao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Flexible job shop scheduling problem (FJSP) is one of the challenging issues in industrial
systems. In this study, we propose a bi-population balancing multi-objective evolutionary …

Flexible job shop scheduling via dual attention network-based reinforcement learning

R Wang, G Wang, J Sun, F Deng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Flexible manufacturing has given rise to complex scheduling problems such as the flexible
job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple …

A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling

Y Du, J Li - International Journal of Production Economics, 2024 - Elsevier
The environmental-friendly production demands higher manufacturing efficiency and lower
energy cost; therefore, time-of-use electricity price constraint and distributed production have …

Q-learning driven multi-population memetic algorithm for distributed three-stage assembly hybrid flow shop scheduling with flexible preventive maintenance

Y Jia, Q Yan, H Wang - Expert Systems with Applications, 2023 - Elsevier
The distributed assembly flow shop scheduling (DAFS) problem has received much
attention in the last decade, and a variety of metaheuristic algorithms have been developed …

Q-learning based multi-objective immune algorithm for fuzzy flexible job shop scheduling problem considering dynamic disruptions

X Chen, J Li, Y Xu - Swarm and Evolutionary Computation, 2023 - Elsevier
Confronted with complex industrial environments, dynamic disruptions like new job arrival
and machine breakdown bring significant challenges to the robustness and stability of the …

An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing

X Wang, L Zhang, Y Liu, Y Laili - International Journal of …, 2024 - Taylor & Francis
Dynamic task scheduling problem in cloud manufacturing (CMfg) is always challenging
because of changing manufacturing requirements and services. To make instant decisions …

A multi-objective optimization algorithm for flow shop group scheduling problem with sequence dependent setup time and worker learning

DN Sekkal, F Belkaid - Expert Systems with Applications, 2023 - Elsevier
The optimization of production systems has become increasingly important in manufacturing
industries due to the growing competition and market demands. One of the overriding …