The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In
addition to exploiting sine and cosine functions to perform local and global searches (hence …

This paper proposes AutoGCOP, a new general framework for automated design of local
search algorithms. In a recently established General Combinatorial Optimisation Problem …

One of the central issues that must be resolved for a metaheuristic optimization process to
work well is the dilemma of the balance between exploration and exploitation. The …

Many Metaheuristics solve optimization problems in the continuous domain, so it is
necessary to apply binarization schemes to solve binary problems, this selection that is not …

With a recently defined AutoGCOP framework, the design of local search algorithms has
been defined as the composition of elementary algorithmic components. The effective …

This paper describes a new hyperheuristic algorithm that performs well over a variety of
different problem classes. A novel method for switching between working on a single …

Heuristics, metaheuristics and hyper-heuristics are search methodologies which have been
preferred by many researchers and practitioners for solving computationally hard …

Ant colony optimization (ACO) is a bio-inspired technique formalized into a meta-heuristic for
combinatorial optimization problems. In this work, the ACO-Otsu segmentation method …

The first Cross-domain Heuristic Search Challenge (CHeSC 2011) is an international
research competition aimed at measuring hyperheuristics performance over several …

Hyperheuristics represent a generic method that provides a high level of abstraction,
enabling solving several problems in the combinatorial optimization domain while reducing …