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A review on representative swarm intelligence algorithms for solving optimization problems: Applications and trends
J Tang, G Liu, Q Pan - IEEE/CAA Journal of Automatica Sinica, 2021 - ieeexplore.ieee.org
Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is
increasing popularity in resolving different optimization problems and has been widely …
increasing popularity in resolving different optimization problems and has been widely …
A survey of job shop scheduling problem: The types and models
H **ong, S Shi, D Ren, J Hu - Computers & Operations Research, 2022 - Elsevier
Job shop scheduling problem (JSSP) is a thriving area of scheduling research, which has
been concerned and studied widely by scholars in engineering and academic fields. This …
been concerned and studied widely by scholars in engineering and academic fields. This …
Flexible job-shop scheduling via graph neural network and deep reinforcement learning
Recently, deep reinforcement learning (DRL) has been applied to learn priority dispatching
rules (PDRs) for solving complex scheduling problems. However, the existing works face …
rules (PDRs) for solving complex scheduling problems. However, the existing works face …
Learning to dispatch for job shop scheduling via deep reinforcement learning
Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling
problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad …
problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad …
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 …
Surprisingly popular-based adaptive memetic algorithm for energy-efficient distributed flexible job shop scheduling
With the development of the economy, distributed manufacturing has gradually become the
mainstream production mode. This work aims to solve the energy-efficient distributed flexible …
mainstream production mode. This work aims to solve the energy-efficient distributed flexible …
Energy-optimized partial computation offloading in mobile-edge computing with genetic simulated-annealing-based particle swarm optimization
Smart mobile devices (SMDs) can meet users' high expectations by executing computational
intensive applications but they only have limited resources, including CPU, memory, battery …
intensive applications but they only have limited resources, including CPU, memory, battery …
Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling
Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …
the production efficiency. JSS has a wide range of applications, such as order picking in the …
Iterated greedy algorithms for flow-shop scheduling problems: A tutorial
An iterated greedy algorithm (IGA) is a simple and powerful heuristic algorithm. It is widely
used to solve flow-shop scheduling problems (FSPs), an important branch of production …
used to solve flow-shop scheduling problems (FSPs), an important branch of production …
A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times
Y Du, J Li, C Li, P Duan - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Flexible job shop scheduling problem (FJSP) has attracted research interests as it can
significantly improve the energy, cost, and time efficiency of production. As one type of …
significantly improve the energy, cost, and time efficiency of production. As one type of …