Scalability of optimization algorithms is a major challenge in coping with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …

A method of heuristically solving large traveling salesman problems is suggested, where a
dramatic computational speedup is guaranteed. A specific genetic algorithm is the solver …

Wolpert and Macready asserted that no single search algorithm is best on average for all
problems, which is confirmed by most practical experiences. Therefore, optimization results …

Cooperative co-evolution (CC) is an evolutionary framework for dealing with large-scale
optimization problems. The divide-and-conquer strategy is widely used in CC. The large …

The active-scan agile earth observation satellite (AS-AEOS) is highly agile in three axis
which enables in-motion imaging, allowing any imaging direction for a given ground target …

Abstract Evolutionary Algorithms (EAs) are a set of optimization techniques that have
become incredibly popular in the last decades. As they are general purpose algorithms, they …

Hyper-heuristics are high level search methodologies that operate over a set of heuristics
which operate directly on the problem domain. In one of the hyper-heuristic frameworks, the …

Evolutionary Algorithms are powerful optimization techniques which have been applied to
many different problems, from complex mathematical functions to real-world applications …

A method of quickly obtaining an approximate solution to the traveling salesman problem
(TSP) is suggested, where a dramatic computational speedup is guaranteed. The initial TSP …

Este trabajo analiza el comportamiento de dos algoritmos distribuidos heterogéneos que
combinan las siguientes técnicas evolutivas: Algoritmos Genéticos (GA), Algoritmos de …