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 …

Hyper-heuristics are search techniques for selecting, generating, and sequencing (meta)-
heuristics to solve challenging optimization problems. They differ from traditional (meta) …

Hyper-heuristics comprise a set of approaches that aim to automate the development of
computational search methodologies. This chapter overviews previous categorisations of …

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 …

Multi-objective optimization allows satisfying multiple decision criteria concurrently, and
generally yields multiple solutions. It has the potential to be applied to structural damage …

Wind farm layout optimisation is a challenging real-world problem which requires the
discovery of trade-off solutions considering a variety of conflicting criteria, such as …

This paper proposed a novel approach for a practical version of the cold chain, namely
location-routing problem-based low-carbon cold chain (LRPLCCC). In the proposed bi …

Metaheuristics, being tailored to each particular domain by experts, have been successfully
applied to many computationally hard optimization problems. However, once implemented …

The benefits of the circular economy are pushing industries towards forming closed-loop
supply chains (CLSCs). This transition requires the industries to deal with conventional cost …

This paper defines a new combinatorial optimization problem, namely General
Combinatorial Optimization Problem (GCOP), whose decision variables are a set of …