Genetic programming for production scheduling: a survey with a unified framework
Genetic programming has been a powerful technique for automated design of production
scheduling heuristics. Many studies have shown that heuristics evolved by genetic …
scheduling heuristics. Many studies have shown that heuristics evolved by genetic …
Automated algorithm selection: Survey and perspectives
It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …
intensely studied, different instances are best solved using different algorithms. This is …
The role of lifelong machine learning in bridging the gap between human and machine learning: A scientometric analysis
Due to advancements in data collection, storage, and processing techniques, machine
learning has become a thriving and dominant paradigm. However, one of its main …
learning has become a thriving and dominant paradigm. However, one of its main …
A classification of hyper-heuristic approaches: revisited
Hyper-heuristics comprise a set of approaches that aim to automate the development of
computational search methodologies. This chapter overviews previous categorisations of …
computational search methodologies. This chapter overviews previous categorisations of …
A multi-task selected learning approach for solving 3D flexible bin packing problem
L Duan, H Hu, Y Qian, Y Gong, X Zhang, Y Xu… - arxiv preprint arxiv …, 2018 - arxiv.org
A 3D flexible bin packing problem (3D-FBPP) arises from the process of warehouse packing
in e-commerce. An online customer's order usually contains several items and needs to be …
in e-commerce. An online customer's order usually contains several items and needs to be …
World Hyper-Heuristic: A novel reinforcement learning approach for dynamic exploration and exploitation
In the real world, there are many complex problems in engineering. Every problem has a
level of computational complexity, starting from simple problems and reaching NP-hard …
level of computational complexity, starting from simple problems and reaching NP-hard …
A hyper-heuristic ensemble method for static job-shop scheduling
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling
problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and …
problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and …
Just-in-time two-dimensional bin packing
This paper considers the on-time guillotine cutting of small rectangular items from large
rectangular bins. Items assigned to a bin define the bins' processing time. Consequently, an …
rectangular bins. Items assigned to a bin define the bins' processing time. Consequently, an …
Automated algorithm selection: from feature-based to feature-free approaches
We propose a novel technique for algorithm-selection, applicable to optimisation domains in
which there is implicit sequential information encapsulated in the data, eg, in online bin …
which there is implicit sequential information encapsulated in the data, eg, in online bin …
Evolutionary hyper-heuristics for tackling bi-objective 2d bin packing problems
In this article, a multi-objective evolutionary framework to build selection hyper-heuristics for
solving instances of the 2D bin packing problem is presented. The approach consists of a …
solving instances of the 2D bin packing problem is presented. The approach consists of a …