Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the
goal of automating the design of heuristic methods to solve hard computational search …

Hyper-heuristics aim at interchanging different solvers while solving a problem. The idea is
to determine the best approach for solving a problem at its current state. This way, every time …

Hyper-heuristics is a fairly recent technique that aims at effectively solving various real-world
optimization problems. This is the first book on hyper-heuristics, and aims to bring together …

The term “hyper-heuristics” is fairly new, although the notion has been hinted at in papers
from time to time since the 1960s (eg Crowston et al., 1963). The key idea is to devise new …

The fields of machine meta-learning and hyper-heuristic optimisation have developed
mostly independently of each other, although evolutionary algorithms (particularly genetic …

In online three-dimensional packing problems (3D-PPs), unlike offline problems, items arrive
sequentially and require immediate packing decisions without any information about the …

We present a number of variants of a constructive algorithm able to solve a wide variety of
variants of the Two-Dimensional Irregular Bin Packing Problem (2DIBPP). The aim of the …

Research on the three-dimensional (3D) packing problem has largely focused on packing
boxes for the transportation of goods. As a result, there has been little focus on packing …

This paper describes a method for solving vehicle routing problems with time windows,
based on selecting meta-heuristics via meta-learning. Although several meta-heuristics …

Genetic programming approaches have been employed in the literature to automatically
design constructive heuristics for cutting and packing problems. These heuristics obtain …