Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …

The optimization performance of differential evolution (DE) algorithm significantly depends
on control parameters and mutation strategy. However, it is difficult to set suitable control …

Differential evolution (DE) is one of the most popular and efficient evolutionary algorithms for
numerical optimization and it has gained much success in a series of academic benchmark …

Differential evolution (DE) is among the most efficient evolutionary algorithms (EAs) for
global optimization and now widely applied to solve diverse real-world applications. As the …

When solving constrained optimization problems (COPs) by evolutionary algorithms, the
search algorithm plays a crucial role. In general, we expect that the search algorithm has the …

In this paper, a new metaheuristic optimization algorithm based on the law of
thermodynamics and heat transfer is introduced. In the proposed algorithm, the search …

For expensive constrained optimization problems (ECOPs), the computation of objective
function and constraints is very time-consuming. This paper proposes a novel global and …

This paper proposes an adaptive elitist differential evolution (aeDE) for optimization of truss
structures with discrete design variables. The aeDE algorithm is a newly improved version of …

This study addresses the growing interest in utilizing steel slag as a sustainable alternative
to river sand in additive manufacturing of concrete, driven by the increasing scarcity of …

Differential evolution is one of the most popular evolutionary algorithms for continuous
optimization. In this paper, we introduce a new algorithm named the adaptive differential …