Quantum Inspired Differential Evolution Algorithm
نویسندگان
چکیده
To enhance the optimization performance of differential evolution algorithm, by studying the implementation mechanism of differential evolution algorithm, a new idea of incorporating differential strategy and rotation of qubits in the Bloch sphere is proposed in this paper. In the proposed approach, the individuals are encoded by qubits described on Bloch sphere, and the rotation angles of qubits in current individual are obtained by differential strategy. The axis of rotation is designed by using vector product theory, and the rotation matrixes are constructed by using Pauli matrixes. Taking the corresponding qubits in current best individual as targets, the qubits in current individual are rotated to the target qubits about the rotation axis on the Bloch sphere. The Hadamard gates are used to mutate individuals. The simulation results of optimizing the minimum value of functions indicate that, for an iterative step, the average time of the proposed approach is 13 times as long as that of the classical differential evolution algorithm. When the same limited steps are applied in two approaches, the average optimization result of the proposed approach is 0.3 times as great as that of the classical differential evolution algorithm; when the same running time is applied in two approaches, the average optimization result of the proposed approach is 0.4 times as great as that of the classical differential evolution algorithm. These results suggest that the proposed approach is inefficient in computational ability; however, it is obviously efficient in optimization ability, and the overall optimization performance is better than that of the classical differential evolution algorithm.
منابع مشابه
A Quantum-Inspired Differential Evolution Algorithm for Rigid Image Registration
In this paper a quantum inspired differential evolution algorithm (QDEA) for image registration is presented. Image registration is a fundamental task in almost every computer vision system. It aims to find the best transformation that allows the superimposing of the common parts of two images. The proposed algorithm is a novel hybridization between differential evolution algorithms and quantum...
متن کاملBQIABC: A new Quantum-Inspired Artificial Bee Colony Algorithm for Binary Optimization Problems
Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...
متن کاملQuantum-Inspired Differential Evolution with Particle Swarm Optimization for Knapsack Problem
This paper presents a new hybrid algorithm called QDEPSO (Quantum inspired Differential Evolution with Particle Swarm Optimization) which combines differential evolution (DE), particle swarm optimization method (PSO) and quantum-inspired evolutionary algorithm (QEA) in order to solve the 0-1 optimization problems. In the initialization phase, the QDEPSO uses the concepts of quantum computing as...
متن کاملComparing the performance of quantum-inspired evolutionary algorithms for the solution of software requirements selection problem
Context: In requirements engineering phase of the software development life cycle, one of the main concerns of software engineers is to select a set of software requirements for implementation in the next release of the software from many requirements proposed by the customers, while balancing budget and customer satisfaction. Objective: To analyse the efficacy of Quantum-inspired Elitist Multi...
متن کاملA Quantum-Inspired Differential Evolution Algorithm for Solving the N-Queens Problem
In this paper, a quantum-inspired differential evolution algorithm for solving the N-queens problem is presented. The N-queens problem aims at placing N queens on an NxN chessboard, in such a way that no queen could capture any of the others. The proposed algorithm is a novel hybridization between differential evolution algorithms and quantum computing principles. Accordingly, differential evol...
متن کاملAn adaptive quantum-inspired differential evolution algorithm for 0-1 knapsack problem
Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces. However, the design of its operators makes it unsuitable for many real-life constrained combinatorial optimization problems which operate on binary space. On the other hand, the quantum inspired evolutionary algorithm (QEA) is ver...
متن کامل