Most real-world problems involve some type of optimization problems that are often
constrained. Numerous researchers have investigated several techniques to deal with …

Natural computing is a terminology introduced to encompass three classes of methods:(1)
those that take inspiration from nature for the development of novel problem-solving …

Energy is a vital resource for human activities and lifestyle, powering important everyday
infrastructures and services. Currently, pollutant and non-renewable sources, such as fossil …

In their original versions, nature-inspired search algorithms such as evolutionary algorithms
and those based on swarm intelligence, lack a mechanism to deal with the constraints of a …

Solving constrained optimization problems (COPs) with evolutionary algorithms (EAs) is a
popular research direction due to its potential and diverse applications. One of the key …

In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to
solve constraint optimization tasks. BA is verified using several classical benchmark …

Evolutionary algorithms have been effectively used to solve multiobjective optimization
problems with a small number of objectives, two or three in general. However, when …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

The ε constrained method is an algorithm transformation method, which can convert
algorithms for unconstrained problems to algorithms for constrained problems using the ε …

During the last three decades, several constraint handling techniques have been developed
to be used with evolutionary algorithms (EAs). According to the no free lunch theorem, it is …