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 …

This article presents a review and a comparative analysis between frameworks for solving
optimization problems using metaheuristics. The aim is to identify both the desirable …

This paper presents HyFlex, a software framework for the development of cross-domain
search methodologies. The framework features a common software interface for dealing with …

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

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

Hyper-heuristics are a class of high-level search technologies to solve computationally
difficult problems which operate on a search space of low-level heuristics rather than …

There is a growing interest towards the design of reusable general purpose search methods
that are applicable to different problems instead of tailored solutions to a single particular …

A variant of the hub location routing problem studied in this work, which is the problem of
locating a set of hub nodes, is establishing the hub-level network and allocating the spoke …

This paper describes a unique meta-heuristic technique for hybridizing bio-inspired heuristic
algorithms. The technique is based on altering the state of agents using a logistic probability …