Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

In view of scarcity of traditional energy resources and environmental issues, renewable
energy resources (RERs) are introduced to fulfill the electricity requirement of growing world …

Many seemingly different problems in machine learning, artificial intelligence, and symbolic
processing can be viewed as requiring the discovery of a computer program that produces …

The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …

This paper proposes a novel evolutionary algorithm inspired by quantum computing, called
a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and …

This paper proposes a novel evolutionary computing method called a genetic quantum
algorithm (GQA). GQA is based on the concept and principles of quantum computing such …

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that
shares many similarities with evolutionary computation techniques. However, the PSO is …

From recent research on combinatorial optimization of the knapsack problem, quantum-
inspired evolutionary algorithm (QEA) was proved to be better than conventional genetic …

Quantum-inspired evolutionary algorithms, one of the three main research areas related to
the complex interaction between quantum computing and evolutionary algorithms, are …

Natural biological systems are selected by evolution to continue to exist and evolve.
Evolution likely gives rise to complicated systems that are difficult to understand and …