[HTML][HTML] Recent advances in selection hyper-heuristics

JH Drake, A Kheiri, E Özcan, EK Burke - European Journal of Operational …, 2020 - Elsevier
Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

Operational research in education

J Johnes - European journal of operational research, 2015 - Elsevier
Operational Research (OR) techniques have been applied, from the early stages of the
discipline, to a wide variety of issues in education. At the government level, these include …

A deep reinforcement learning based hyper-heuristic for combinatorial optimisation with uncertainties

Y Zhang, R Bai, R Qu, C Tu, J ** - European Journal of Operational …, 2022 - Elsevier
In the past decade, considerable advances have been made in the field of computational
intelligence and operations research. However, the majority of these optimisation …

A classification of hyper-heuristic approaches: revisited

EK Burke, MR Hyde, G Kendall, G Ochoa… - Handbook of …, 2019 - Springer
Hyper-heuristics comprise a set of approaches that aim to automate the development of
computational search methodologies. This chapter overviews previous categorisations of …

Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms

MM Drugan - Swarm and evolutionary computation, 2019 - Elsevier
A variety of Reinforcement Learning (RL) techniques blends with one or more techniques
from Evolutionary Computation (EC) resulting in hybrid methods classified according to their …

LS-HH: A learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling

Z Shao, W Shao, D Pi - IEEE Transactions on Emerging Topics …, 2022 - ieeexplore.ieee.org
As the development of economic globalization, the distributed manufacturing has become
common in modern industries. The scheduling of production resources in multiple …

A hybrid algorithm for the university course timetabling problem using the improved parallel genetic algorithm and local search

A Rezaeipanah, SS Matoori, G Ahmadi - Applied Intelligence, 2021 - Springer
Scheduling is one of the problems that has attracted the attention of many researchers over
the years. The University Course Timetabling Problem (UCTP) is a highly constrained real …

A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup …

Z Shao, W Shao, J Chen, D Pi - Engineering Applications of Artificial …, 2024 - Elsevier
Distributed manufacturing is increasingly common due to economic globalization. It has
important practical significance to optimize global supply chains by considering cooperative …

[PDF][PDF] Application of simulated annealing in various field

C Venkateswaran, M Ramachandran… - Materials and its …, 2022 - academia.edu
Simulated annealing is a method of solving uncontrolled and controlled optimization
problems. This method simulates the physical process of heating an object and then slowly …

A review of hyper-heuristics for educational timetabling

N Pillay - Annals of Operations Research, 2016 - Springer
Educational timetabling problems, namely, university examination timetabling, university
course timetabling and school timetabling, are combinatorial optimization problems …