In this contribution, a novel bionic algorithm inspired by plant root foraging behaviors,
namely artificial root foraging optimization (ARFO) algorithm, is designed and developed …

Differential evolution (DE) is recognized as a simplistic yet robust evolutionary algorithm: it
has been utilized to tackle different challenging optimization problems in various science …

We propose a novel simple variant of differential evolution (DE) algorithm and call it TVDE
because it is a time-varying strategy-based DE algorithm. In our TVDE, three functions with …

This study presented a new multi-species binary coded algorithm, Mendelian evolutionary
theory optimization (METO), inspired by the plant genetics. This framework mainly consists …

This paper designed an advanced hybrid algorithm (h aDEPSO) to solve the optimization
problems, based on multi-population approach. It integrated with suggested advanced DE …

D-optimal designs are frequently used in controlled experiments to obtain the most accurate
estimate of model parameters at minimal cost. Finding them can be a challenging task …

Differential evolution (DE) is an evolutionary algorithm that is straightforward but effective
and has been satisfactorily implemented in a variety of fields. However, the DE relies heavily …

Particle swarm optimization (PSO) and differential evolution (DE) are two efficient meta-
heuristic algorithms, achieving excellent performance in a wide variety of optimization …

To solve multi-modal optimization problems, the niching technique is widely used because it
could find and preserve multiple stable sub-populations. However, the performances of most …

Differential Evolution (DE) is a readily comprehensible and highly powerful intelligent
optimized method for numerical optimization. The performance of DE significantly depends …