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

The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …

Metaheuristics have yielded very promising results for the frequency assignment problem
(FAP). However, the results obtainable using currently published methods are far from ideal …

Hyper-heuristics introduce novel approaches for solving challenging combinatorial
optimization problems by operating over a set of low level (meta)-heuristics. This is achieved …

This work presents a set of approaches used to deal with the Frequency Assignment
Problem (FAP), which is one of the key issues in the design of Global System for Mobile …

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding
robust and reliable solutions that are less sensitive to stochastic behaviours of customer …

Premature convergence is one of the most important recurrent drawbacks of Evolutionary
Algorithms and other metaheuristics. As a result, several methods to alleviate this problem …

Bin Packing problems are NP-hard problems with many practical applications. A variant of a
Bin Packing Problem was proposed in the GECCO 2008 competition session. The best …

Abstract The Frequency Assignment Problem (fap) is one of the key issues in the design of
Global System for Mobile Communications (gsm) networks. The formulation of the fap used …

One of the most commonly known weaknesses of Evolutionary Algorithms (eas) is the large
dependency between the values selected for their parameters and the results. Parameter …