More than a decade after the first extensive overview on parameter control, we revisit the
field and present a survey of the state-of-the-art. We briefly summarize the development of …

Evolutionary algorithms (EAs) are robust stochastic optimisers that perform well over a wide
range of problems. Their robustness, however, may be affected by several adjustable …

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 …

Optimal power flow (OPF) is a highly non-linear complex optimization problem where the
steady state parameters of an electrical network need to be determined for its economical …

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 …

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 …

This article presents a new constraint-handling technique (CHT), called shift-based penalty
(ShiP), for solving constrained multiobjective optimization problems. In ShiP, infeasible …

We propose a novel hybrid algorithm named PSO-DE, which integrates particle swarm
optimization (PSO) with differential evolution (DE) to solve constrained numerical and …

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 …

An efficient optimization algorithm called teaching–learning-based optimization (TLBO) is
proposed in this article to solve continuous unconstrained and constrained optimization …