A hybrid quantum inspired harmony search algorithm for 0–1 optimization problems

Layeb, Abdesslem

doi:10.1016/j.cam.2013.04.004

Cited by 96 publications

(39 citation statements)

References 17 publications

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“…An application to image thresholding using quantum ant colony optimization is reported in [55]. Two quantum binarization applications to the knapsack problem are reported previously using harmony search in [58] and monkey algorithm in [59]. The quantum differential evolution algorithm was applied to the knapsack problem in [53], combinatorial problems [54], and image threshold methods in [55].…”

Section: Binarization Methodsmentioning

confidence: 99%

“…A 4 Complexity quantum ant colony optimization was applied to image threshold in [55]. Using Harmony Search in [58] and Monkey algorithm in [59], quantum binarizations were applied to the knapsack problem. The unsupervised learning K-means clustering method is used to perform binarization in different problems as is shown in Figure 1.…”

Section: Binarization Methodsmentioning

confidence: 99%

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A Binary Cuckoo Search Big Data Algorithm Applied to Large‐Scale Crew Scheduling Problems

et al. 2018

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The progress of metaheuristic techniques, big data, and the Internet of things generates opportunities to performance improvements in complex industrial systems. This article explores the application of Big Data techniques in the implementation of metaheuristic algorithms with the purpose of applying it to decision-making in industrial processes. This exploration intends to evaluate the quality of the results and convergence times of the algorithm under different conditions in the number of solutions and the processing capacity. Under what conditions can we obtain acceptable results in an adequate number of iterations? In this article, we propose a cuckoo search binary algorithm using the MapReduce programming paradigm implemented in the Apache Spark tool. The algorithm is applied to different instances of the crew scheduling problem. The experiments show that the conditions for obtaining suitable results and iterations are specific to each problem and are not always satisfactory.

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Section: Binarization Methodsmentioning

confidence: 99%

Section: Binarization Methodsmentioning

confidence: 99%

A Binary Cuckoo Search Big Data Algorithm Applied to Large‐Scale Crew Scheduling Problems

et al. 2018

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“…In order to evaluate the performance of the proposed TDDE algorithm for solving 0-1 knapsack problems, twenty 0-1 knapsack test instances are produced by using the method as recommended by [4], which is widely used in the field of 0-1 knapsack problem research [15,16,19]. To generate each 0-1 knapsack test instance, we randomly generate the weight W j and profit P j for item j, where j = 1, · · · , D; W j is a uniformly distributed random number in the range [5,20], P j is randomly generated from a uniform distribution in the range [50,100] and the maximum weight capacity of a knapsack C is set to:…”

Section: Methodsmentioning

confidence: 99%

A Thermodynamical Selection-Based Discrete Differential Evolution for the 0-1 Knapsack Problem

Guo

Yue

Zhang

et al. 2014

Entropy

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Many problems in business and engineering can be modeled as 0-1 knapsack problems. However, the 0-1 knapsack problem is one of the classical NP-hard problems. Therefore, it is valuable to develop effective and efficient algorithms for solving 0-1 knapsack problems. Aiming at the drawbacks of the selection operator in the traditional differential evolution (DE), we present a novel discrete differential evolution (TDDE) for solving 0-1 knapsack problem. In TDDE, an enhanced selection operator inspired by the principle of the minimal free energy in thermodynamics is employed, trying to balance the conflict between the selective pressure and the diversity of population to some degree. An experimental study is conducted on twenty 0-1 knapsack test instances. The comparison results show that TDDE can gain competitive performance on the majority of the test instances.

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“…Quantum theory is an ongoing research in the fields of quick search [20], optimization [21,22], clustering [23], and key distribution [24]. The work of incorporating quantum mechanics into other theories has stimulated the researches of quantum-inspired algorithms and their applications.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Vibration Signal Denoising Using Quantum‐Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model

Huang

Chen

et al. 2018

Shock and Vibration

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Aiming at improving noise reduction effect for mechanical vibration signal, a Gaussian mixture model (SGMM) and a quantuminspired standard deviation (QSD) are proposed and applied to the denoising method using the thresholding function in wavelet domain. Firstly, the SGMM is presented and utilized as a local distribution to approximate the wavelet coefficients distribution in each subband. Then, within Bayesian framework, the maximum a posteriori (MAP) estimator is employed to derive a thresholding function with conventional standard deviation (CSD) which is calculated by the expectation-maximization (EM) algorithm. However, the CSD has a disadvantage of ignoring the interscale dependency between wavelet coefficients. Considering this limit for the CSD, the quantum theory is adopted to analyze the interscale dependency between coefficients in adjacent subbands, and the QSD for noise-free wavelet coefficients is presented based on quantum mechanics. Next, the QSD is constituted for the CSD in the thresholding function to shrink noisy coefficients. Finally, an application in the mechanical vibration signal processing is used to illustrate the denoising technique. The experimental study shows the SGMM can model the distribution of wavelet coefficients accurately and QSD can depict interscale dependency of wavelet coefficients of true signal quite successfully. Therefore, the denoising method utilizing the SGMM and QSD performs better than others.

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A hybrid quantum inspired harmony search algorithm for 0–1 optimization problems

Cited by 96 publications

References 17 publications

A Binary Cuckoo Search Big Data Algorithm Applied to Large‐Scale Crew Scheduling Problems

A Binary Cuckoo Search Big Data Algorithm Applied to Large‐Scale Crew Scheduling Problems

A Thermodynamical Selection-Based Discrete Differential Evolution for the 0-1 Knapsack Problem

Mechanical Vibration Signal Denoising Using Quantum‐Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model

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