Metaheuristic optimization algorithms (MOAs) are computational randomized search
processes which draw inspiration from physical and biological phenomena, with an …

This paper provides a survey of the most important repair heuristics used in evolutionary
algorithms to solve constrained optimization problems. Popular techniques are reviewed …

This paper presents a new optimization technique called water cycle algorithm (WCA) which
is applied to a number of constrained optimization and engineering design problems. The …

Purpose–Nature‐inspired algorithms are among the most powerful algorithms for
optimization. The purpose of this paper is to introduce a new nature‐inspired metaheuristic …

A novel population-based algorithm based on the mine bomb explosion concept, called the
mine blast algorithm (MBA), is applied to the constrained optimization and engineering …

Multi-population algorithms have been widely used for solving the real-world problems.
However, it is not easy to get the number of sub-populations to be used for a given problem …

This contribution summarizes the design and analysis of experiments with computerized
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …

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 …

This paper details a proposed demand response (DR) application to optimize the operation
of appliances in an indeterminate environment in a home energy management system. An …