A learning-based memetic algorithm for energy-efficient flexible job-shop scheduling with type-2 fuzzy processing time
Green flexible job-shop scheduling problem (FJSP) aims to improve profit and reduce
energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy …
energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy …
Estimation of distribution algorithms in machine learning: a survey
P Larrañaga, C Bielza - IEEE Transactions on Evolutionary …, 2023 - ieeexplore.ieee.org
The automatic induction of machine learning models capable of addressing supervised
learning, feature selection, clustering and reinforcement learning problems requires …
learning, feature selection, clustering and reinforcement learning problems requires …
Precast production scheduling in off-site construction: Mainstream contents and optimization perspective
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 …
(OSC) and has received considerable attention from researchers. However, there is still a …
Co-evolution with deep reinforcement learning for energy-aware distributed heterogeneous flexible job shop scheduling
Energy-aware distributed heterogeneous flexible job shop scheduling (DHFJS) problem is
an extension of the traditional FJS, which is harder to solve. This work aims to minimize total …
an extension of the traditional FJS, which is harder to solve. This work aims to minimize total …
RL-GA: A reinforcement learning-based genetic algorithm for electromagnetic detection satellite scheduling problem
The study of electromagnetic detection satellite scheduling problem (EDSSP) has attracted
attention due to the detection requirements for a large number of targets. This paper …
attention due to the detection requirements for a large number of targets. This paper …
Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation
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 …
systems. In this study, we propose a bi-population balancing multi-objective evolutionary …
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 …
energy cost; therefore, time-of-use electricity price constraint and distributed production have …
A learning-based multipopulation evolutionary optimization for flexible job shop scheduling problem with finite transportation resources
In many practical manufacturing systems, transportation equipment such as automated
guided vehicles (AGVs) is widely adopted to transfer jobs and realize the collaboration of …
guided vehicles (AGVs) is widely adopted to transfer jobs and realize the collaboration of …
Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
Evolutionary algorithms (EA), a class of stochastic search methods based on the principles
of natural evolution, have received widespread acclaim for their exceptional performance in …
of natural evolution, have received widespread acclaim for their exceptional performance in …
Solving flexible job shop scheduling problems via deep reinforcement learning
Flexible job shop scheduling problem (FJSSP), as a variant of the job shop scheduling
problem, has a larger solution space. Researchers are always looking for good methods to …
problem, has a larger solution space. Researchers are always looking for good methods to …