Quantum-inspired Evolutionary Algorithm: A Survey
نویسندگان
چکیده
منابع مشابه
Quantum - inspired Evolutionary Algorithm
This thesis proposes a novel evolutionary algorithm inspired by quantum computing, called a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QEA is also characterized by the representation of the individual, the evaluation function, and the popu...
متن کاملA Retroactive Quantum-inspired Evolutionary Algorithm
This study outlines some weaknesses of existing Quantum-inspired Evolutionary Algorithms (QEA) by explaining how a bad choice of the rotation angle of qubit quantum gates can slow down optimal solutions discovery. A new algorithm, called Retroactive Quantum inspired Evolutionary Algorithm (rQEA), is proposed. With rQEA the rotation of individual’s amplitudes is performed by quantum gates accord...
متن کاملSurvey of Quantum-Inspired Evolutionary Algorithms
This paper presents a concise survey of a new class of metaheuristics, drawing their inspiration from both: biological evolution and unitary evolution of quantum systems. In the first part of the paper, general concepts behind quantum-inspired evolutionary algorithms have been presented. In the second part, a state of the art of this field has been discussed and a literature review has been con...
متن کاملQuantum-Inspired Evolutionary Algorithm-Based Face Verification
Face verification is considered to be the main part of the face detection system. To detect human faces in images, face candidates are extracted and face verification is performed. This paper proposes a new face verification algorithm using Quantum-inspired Evolutionary Algorithm (QEA). The proposed verification system is based on Principal Components Analysis (PCA). Although PCA related algori...
متن کاملMeta-optimization of Quantum-Inspired Evolutionary Algorithm
In this paper, a meta-optimization algorithm, based on Local Unimodal Sampling (LUS), has been applied to tune selected parameters of QuantumInspired Evolutionary Algorithm for numerical optimization problems coded in real numbers. Tuning of the following two parameters has been considered: crossover rate and contraction factor. Performance landscapes of the algorithm meta-fitness have been app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: DEStech Transactions on Engineering and Technology Research
سال: 2017
ISSN: 2475-885X
DOI: 10.12783/dtetr/mimece2016/10026