Nature-inspired optimization relies on the observation of the efficacy of natural mechanisms for achieving optimal results in the case of processes of vital importance. What is imitated in this case belong to the macroscopic world. However, nature operates with the same efficacy also at the microscopic level, where the laws governing it are those of quantum mechanics. Hence, it is quite reasonable to investigate at this level the possibility of obtaining efficacious optimization algorithms. In the present chapter, a quantum algorithm is proposed for solving a basic problem related to optimization: the determination of the maximum (minimum) in a set of positive integers. The suggested algorithm solves the said problem by an exhaustive procedure based on a suitable nonlinear quantum operator. An example illustrates the details of the algorithm. © 2011 by Nova Science Publishers, Inc. All rights reserved.
Exploiting Quantum Entanglement and Quantum Superposition for Nature-Inspired Optimization / Panella, Massimo. - STAMPA. - (2012), pp. 249-264.
Exploiting Quantum Entanglement and Quantum Superposition for Nature-Inspired Optimization
PANELLA, Massimo
2012
Abstract
Nature-inspired optimization relies on the observation of the efficacy of natural mechanisms for achieving optimal results in the case of processes of vital importance. What is imitated in this case belong to the macroscopic world. However, nature operates with the same efficacy also at the microscopic level, where the laws governing it are those of quantum mechanics. Hence, it is quite reasonable to investigate at this level the possibility of obtaining efficacious optimization algorithms. In the present chapter, a quantum algorithm is proposed for solving a basic problem related to optimization: the determination of the maximum (minimum) in a set of positive integers. The suggested algorithm solves the said problem by an exhaustive procedure based on a suitable nonlinear quantum operator. An example illustrates the details of the algorithm. © 2011 by Nova Science Publishers, Inc. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.