Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …

Many swarm optimization algorithms have been introduced since the early 60's,
Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms …

This paper presents a new variant of the Differential Evolution (DE) algorithm called
Sinusoidal Differential Evolution (SinDE). The key idea of the proposed SinDE is the use of …

This work proposes a metaphor-less and algorithm-specific parameter-less algorithm,
named as self-adaptive population Rao algorithm, for solving the single-, multi-, and many …

The current study unveils an analytical dynamic model of a parabolic trough solar collector
(PTSC) and subsequently presents the process to derive the transfer function of the PTSC …

Rock mechanical properties play a key role in the optimization process of engineering
practices in the oil and gas industry so that better field development decisions can be made …

The current study analyzes the potential of an environmentally benign integration of a
parabolic trough solar collector (PTSC) with a heat-intensive multi-effect evaporator (MEE) …

Swarm based algorithms play a very important role in solving optimization problems as
these algorithms perform better than the traditional techniques. Various such swarm-based …

The differential evolution (DE) algorithm is a simple but powerful population-based
stochastic search technique for solving global optimization problems. DE consists of three …

Differential evolution (DE) is an evolutionary algorithm (EA) that uses a rather greedy and
less stochastic approach to solve optimization problems than other evolutionary methods [1] …