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 …

Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in
practice, it is difficult to choose one appropriately for several reasons. First and …

This paper proposes a novel surrogate ensemble-assisted hyper-heuristic algorithm (SEA-
HHA) to solve expensive optimization problems (EOPs). A representative HHA consists of …

Metaheuristics have become a widely used approach for solving a variety of practical
problems. The literature is full of diverse metaheuristics based on outstanding ideas and …

This paper proposes a novel hyper-heuristic algorithm termed evolutionary multi-mode slime
mold optimization (EMSMO) for addressing continuous optimization problems. The …

Hyper-heuristics (HHs) stand as a relatively recent approach to solving optimization
problems. There are different kinds of HHs. One of them deals with how low-level heuristics …

Recent years have witnessed a growing interest in automatic learning mechanisms and
applications. The concept of hyper-heuristics, algorithms that either select among existing …

Metaheuristic algorithms are constructed to solve optimization problems, but they cannot
solve all the problems with best solutions. This work proposes a novel self-adaptive …

Optimisation has been with us since before the first humans opened their eyes to natural
phenomena that inspire technological progress. Nowadays, it is quite hard to find a solver …

There is a colourful palette of metaheuristics for solving continuous optimisation problems in
the literature. Unfortunately, it is not easy to pick a suitable one for a specific practical …