Research into the applicability of ant-based optimisation techniques for hyper-heuristics is
largely limited. This paper expands upon the existing body of research by presenting a novel …

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

The literature shows that one-, two-, and three-dimensional bin packing and knapsack
packing are difficult problems in operational research. Many techniques, including exact …

A hyperheuristic is a high level problem solving methodology that performs a search over
the space generated by a set of low level heuristics. One of the hyperheuristic frameworks is …

The knapsack problem is a fundamental problem that has been extensively studied in
combinatorial optimization. The reason is that such a problem has many practical …

Recent years have witnessed the great success of hyper-heuristics applying to numerous
real-world applications. Hyper-heuristics raise the generality of search methodologies by …

Several metaheuristics have been developed for global optimization. Most of them are
designed for solving a specific problem at hand, and their use on a new implementation is a …

The bin packing problem is a widespread combinatorial problem. It aims at packing a set of
items by using as few bins as possible. Among the many available solving methods …

Hyper-heuristics are new approaches which aim at raising the level of abstraction when
solving combinatorial optimisation problems. In this paper we introduce a new hyper …

Recent years have witnessed great success of ant based hyper heuristics applying to real
world applications. Ant based hyper heuristics intend to explore the heuristic space by …