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

In the era of industry 4.0, artificial intelligence (AI) may potentially be used to provide
reasoning and decision support on engineering and technical challenges. The role of AI in …

Hybrid metaheuristics are of the most interesting recent trends in optimization and memetic
algorithms. In this paper, two hybridization models are used to design different feature …

The development and application of evolutionary algorithms (EAs) and other metaheuristics
for the optimisation of water resources systems has been an active research field for over …

Cooperative co-evolution has been introduced into evolutionary algorithms with the aim of
solving increasingly complex optimization problems through a divide-and-conquer …

A unified view of metaheuristics This book provides a complete background on
metaheuristics and shows readers how to design and implement efficient algorithms to solve …

In evolutionary computation, the fitness function normally measures progress toward an
objective in the search space, effectively acting as an objective function. Through deception …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

Genetic algorithms have been used in science and engineering as adaptive algorithms for
solving practical problems and as computational models of natural evolutionary systems …

Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and
sharing have been criticized mainly for:(1) their O (MN/sup 3/) computational complexity …