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) …

A hyper-heuristic algorithm is a general solution framework that adaptively selects the
optimizer to address complex problems. A classical hyper-heuristic framework consists 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 …

Following decades of sustained improvement, metaheuristics are one of the great success
stories of optimization research. However, in order for research in metaheuristics to avoid …

The distributed assembly blocking flow shop scheduling problem, which is a significant
scenario in modern supply chains and manufacturing systems, has attracted significant …

Multi-mode resource and precedence-constrained project scheduling is a well-known
challenging real-world optimisation problem. An important variant of the problem requires …

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 …

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 …