Motivated by the hunting strategies of cheetahs, this paper proposes a nature-inspired
algorithm called the cheetah optimizer (CO). Cheetahs generally utilize three main …

A number of modern metaheuristic optimization techniques are being exploited to work out a
single-objective economic dispatch (ED) problem. The dispatch problems even become …

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm and it
has attracted a large number of widespread researchers. As a branch of PSO, a probabilistic …

As a result of today's rapid socioeconomic growth and environmental concerns, higher
service reliability, better power quality, increased energy efficiency and energy …

Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from
quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization …

Recently, the use of wind generation has rapidly increased in micro-grids. Due to the
fluctuation of wind power, it is difficult to schedule wind turbines (WTs) with other distributed …

This paper presents a hybrid differential evolution (DE) with quantum-behaved particle
swarm optimization (QPSO) for the unmanned aerial vehicle (UAV) route planning on the …

A new variant of particle swarm optimization (PSO), named phase angle-encoded and
quantum-behaved particle swarm optimization (θ-QPSO), is proposed. Six versions of θ …

This paper proposes a new binary particle swarm optimization (BPSO) approach inspired by
quantum computing, namely quantum-inspired BPSO (QBPSO). Although BPSO-based …

This paper presents the design and application of an efficient hybrid heuristic search method
to solve the practical economic dispatch problem considering many nonlinear characteristics …