This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

In 1995 the Handbook of Global Optimization (first volume), edited by R. Horst, and PM
Pardalos, was published. This second volume of the Handbook of Global Optimization is …

Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations
have become state of the art in algorithm design for solving real-world optimization …

The genetic algorithm (GA) is a search heuristic that is routinely used to generate useful
solutions to optimization and search problems. It generates solutions to optimization …

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms
Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by …

Optimization problems abound in most fields of science, engineering, and tech nology. In
many of these problems it is necessary to compute the global optimum (or a good …

The first systematic overviews on global optimization appeared in 1975–1978 thanks to two
fundamental volumes titled Towards Global Optimization (Dixon & Szegö, 1975, 1978). At …

This paper discusses the trade-off between accuracy, reliability and computing time in global
optimization. Particular compromises provided by traditional methods (Quasi-Newton and …

The goal of global optimization is to minimize (or maximize) an objective function over its
entire domain. Heuristic methods such as evolutionary algorithms and simulated annealing …

Most books about global optimization describe the theory of the algorithms, whereas a given
implementation's quality never depends exclusively on the theoretical soundness of the …