A survey of university course timetabling problem: perspectives, trends and opportunities

MC Chen, SL Goh, NR Sabar, G Kendall - IEEE Access, 2021 - ieeexplore.ieee.org
The timetabling problem is common to academic institutions such as schools, colleges or
universities. It is a very hard combinatorial optimisation problem which attracts the interest of …

A novel cooperative multi-stage hyper-heuristic for combination optimization problems

F Zhao, S Di, J Cao, J Tang - Complex System Modeling and …, 2021 - ieeexplore.ieee.org
A hyper-heuristic algorithm is a general solution framework that adaptively selects the
optimizer to address complex problems. A classical hyper-heuristic framework consists of …

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 …

Meta-Black-Box optimization for evolutionary algorithms: Review and perspective

X Yang, R Wang, K Li, H Ishibuchi - Swarm and Evolutionary Computation, 2025 - Elsevier
Abstract Black-Box Optimization (BBO) is increasingly vital for addressing complex real-
world optimization challenges, where traditional methods fall short due to their reliance on …

A decomposition-based multi-objective genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem

L Zhu, J Lin, YY Li, ZJ Wang - Knowledge-based systems, 2021 - Elsevier
In this paper, an efficient decomposition-based multi-objective genetic programming hyper-
heuristic (MOGP-HH/D) approach is proposed for the multi-skill resource constrained project …

Parallel hyper heuristic algorithm based on reinforcement learning for the corridor allocation problem and parallel row ordering problem

J Liu, Z Zhang, S Liu, Y Zhang, T Wu - Advanced Engineering Informatics, 2023 - Elsevier
Hyper heuristics is a relatively new optimisation algorithm. Numerous studies have reported
that hyper heuristics are well applied in combinatorial optimisation problems. As a classic …

Q-learning-based hyper-heuristic evolutionary algorithm for the distributed assembly blocking flowshop scheduling problem

ZQ Zhang, B Qian, R Hu, JB Yang - Applied Soft Computing, 2023 - Elsevier
Distributed shop scheduling problems (DSSPs) have attracted increasing interest in recent
years due to the technical trends of smart manufacturing and Industry 4.0. The distributed …

Multicriteria semi-supervised hyperspectral band selection based on evolutionary multitask optimization

J Shi, X Zhang, X Liu, Y Lei, G Jeon - Knowledge-Based Systems, 2022 - Elsevier
Band selection is a direct and effective method to reduce the spectral dimension, which is
one of popular topics in hyperspectral remote sensing. Compared with unsupervised band …

[HTML][HTML] Optimizing additive manufacturing path pattern for Ti-6Al-4V thin rods using a combinatorial radial basis function surrogate-assisted genetic algorithm

R Bai, G Liang, H Cheng, H Naceur, D Coutellier… - Materials & Design, 2023 - Elsevier
Path pattern is one of the most significant parameters in the additive manufacturing (AM)
process because it influences the specimen's final shape and residual stress distribution …

Radio resource allocation in a 6G D-OMA network with imperfect SIC: A framework aided by a bi-objective hyper-heuristic

FO Torres, VAS Júnior, DB da Costa… - … Applications of Artificial …, 2023 - Elsevier
In the sixth generation (6G) of mobile communication networks, radio resource allocation
management (RRAM) systems must offer high levels of customization and sustainability in …