Qga: a Quantum Genetic Algorithm
نویسندگان
چکیده
The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to non–local or time–dependent fitness functions, is O (N log N) where N is the size of the population. Quantum Genetic Algorithm (QGA) exploits the power of quantum computation in order to speed up genetic procedures. In QGA the classical fitness evaluation and selection procedures are replaced by a single quantum procedure. QGA outperforms a typical classical genetic algorithm. We show that the complexity of our QGA is O (1) in terms of number of oracle calls in the selection procedure. Such theoretical results are confirmed by the simulations of the algorithm.
منابع مشابه
Comparison of genetic algorithm and quantum genetic algorithm
Evolving solutions rather than computing them certainly represents a promising programming approach. Evolutionary computation has already been known in computer science since more than 4 decades. More recently, another alternative of evolutionary algorithms was invented: Quantum Genetic Algorithms (QGA). In this paper, we outline the approach of QGA by giving a comparison with Conventional Gene...
متن کاملParallel Quantum-inspired Genetic Algorithm for Combinatorial Optimization Problem
This paper proposes a new parallel evolutionary algorithm called parallel quantum-inspired genetic algorithm (PQGA). Quantum-inspired genetic algorithm(QGA) is based on the concept and principles of quantum computing such as qubits and superposition of states. Instead of binary, numeric, or symbolic representation, by adopting qubit chromosome as a representation, QGA can represent a linear sup...
متن کاملQuantum Genetic Learning Control of Quantum Ensembles with Hamiltonian Uncertainties
In this paper, a new method for controlling a quantum ensemble that its members have uncertainties in Hamiltonian parameters is designed. Based on combining the sampling-based learning control (SLC) and a new quantum genetic algorithm (QGA) method, the control of an ensemble of a two-level quantum system with Hamiltonian uncertainties is achieved. To simultaneously transfer the ensemble members...
متن کاملMultilevel edge detection using quantum and classical genetic algorithms: A comparative study
In this work, we develop a multilevel edge detection method based on the Kapur and Tsallis entropies. The multilevel thresholding approach gives rise to an NP-hard optimization problem. We have used the Classical Genetic Algorithm (CGA) and the Quantum Genetic Algorithm (QGA) to solve this problem. The performance of the QGA has been tested on ten sample images and it is shown that the QGA outp...
متن کاملA Novel Variant of QGA with VNS for Flowshop Scheduling Problem
In this paper, scheduling problem of flowshop with the criterion of minimizing the total flow time has been considered. An effective hybrid Quantum Genetic Algorithm and Variable Neighborhood Search (QGA-VNS or QGAVNS) has been proposed as solution of Flow Shop Scheduling Problem (FSSP). First, the QGA is considered for global search in optimal solution and then VNS has been integrated for enha...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004