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 …

Initialization of metaheuristics is a crucial topic that lacks a comprehensive and systematic
review of the state of the art. Providing such a review requires in‐depth study and …

It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …

Fitness landscapes were proposed in 1932 as an abstract notion for understanding
biological evolution and were later used to explain evolutionary algorithm behaviour. The …

In the last few decades, genetic algorithms (GAs) demonstrated to be an effective approach
for solving real-world optimization problems. However, it is known that, in presence of a …

Among the existing global optimization algorithms, Particle Swarm Optimization (PSO) is
one of the most effective methods for non-linear and complex high-dimensional problems …

This survey compiles ideas and recommendations from more than a dozen researchers with
different backgrounds and from different institutes around the world. Promoting best practice …

Abstract Population size of Differential Evolution (DE) algorithms is often specified by user
and remains fixed during run. During the first decade since the introduction of DE the …

A variety of Reinforcement Learning (RL) techniques blends with one or more techniques
from Evolutionary Computation (EC) resulting in hybrid methods classified according to their …

Selecting the most appropriate algorithm to use when attempting to solve a black-box
continuous optimization problem is a challenging task. Such problems typically lack …