A cloud model based DNA genetic algorithm for numerical optimization problems

Zang, Wenke; Ren, Liyan; Zhang, Wenqian; Liu, Xiyu

doi:10.1016/j.future.2017.07.036

Cited by 55 publications

(22 citation statements)

References 18 publications

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“…where the parameter k in Equation (10) may be changed based on the fuzziness and randomness of the indicators evaluated [24]. A larger He, as mentioned above, indicates greater randomness of assessment indicators; a smaller He suggests less randomness of the assessment indicators and randomness that is more easily lost [42]. Usually, k is no more than one third, and we set k = 0.1 in this treatment according to reference [22].…”

Section: Input Cloud Drops X Imentioning

confidence: 99%

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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Safety assessment of a casting workshop will provide a clearer understanding of the important safety level required for a foundry. The main purpose of this study was to construct a composite safety assessment method to protect employee health using the cloud model and cause and effect–Layer of Protection Analysis (LOPA). In this study, the weights of evaluation indicators were determined using the subjective analytic hierarchy process and objective entropy weight method respectively. Then, to obtain the preference coefficient of the integrated weight more precisely, a new algorithm was proposed based on the least square method. Next, the safety level of the casting workshop was presented based on the qualitative and quantitative analysis of the cloud model, which realized the uncertainty conversion between qualitative concepts and their corresponding quantitative values, as well as taking the fuzziness and randomness into account; the validity of cloud model evaluation was validated by grey relational analysis. In addition, cause and effect was used to proactively identify factors that may lead to accidents. LOPA was used to correlate corresponding safety measures to the identified risk factors. 6 causes and 19 sub-causes that may contribute to accidents were identified, and 18 potential remedies, or independent protection layers (IPLs), were described as ways to protect employee health in foundry operations. A mechanical manufacturing business in Hunan, China was considered as a case study to demonstrate the applicability and benefits of the proposed safety assessment approach.

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Section: Input Cloud Drops X Imentioning

confidence: 99%

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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“…Flexibility, the ability to work with continuous and discrete variables, handling large search space, providing multiple good solutions, and potential for applying parallel computing techniques are the advantages of this method compared to other meta‐heuristics to reduce the processing time . However, it simply gets stuck at a local optimum and often has slow convergent speed . Due to the advantages of GA, it has been broadly applied in the fields of computer science, social science, and engineering …”

Section: Service Composition Strategiesmentioning

confidence: 99%

“…131 However, it simply gets stuck at a local optimum and often has slow convergent speed. 132 Due to the advantages of GA, it has been broadly applied in the fields of computer science, social science, and engineering. 133…”

Section: Summary Of the Reviewed Bco-based Techniquesmentioning

confidence: 99%

Nature inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments

Asghari

Navimipour

2018

Int J Communication

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Summary Many sorts of services in the cloud environments must be composited based on the user's requests to meet the requirements. Thus, the distributed services are joined to the cloud services through service composition. Also, it is known as NP‐hard problems and many researchers significantly are focused on this problem in recent years. Therefore, many different nature‐inspired meta‐heuristic techniques are proposed for solving this problem. The nature‐inspired meta‐heuristic techniques have an important role in solving the service composition problem in the cloud environments, but there is not a wide‐ranging and detailed paper about reviewing and studying the important mechanisms in this field. Therefore, this study presents a comprehensive analysis of the nature‐inspired meta‐heuristic techniques for the service composition issue in the cloud computing. The review also contains a classification of the important techniques. These classifications include Ant Colony Optimization, Bee Colony Optimization, Genetic Algorithm, Particle Swarm Optimization, Cuckoo Optimization Algorithm, Bat Algorithm, greedy algorithm, and hybrid algorithm. An important aim of this paper is to highlight the emphasis on the optimization algorithms, and the benefits to tackle the challenges are encountered in the cloud service composition. Also, this paper presents the advantages and disadvantages of the nature‐inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments. Moreover, this paper aims to provide more efficient service composition algorithms in the future. Finally, the obtained results have shown that the discussed algorithms have an important effect in solving the cloud service composition problem, and this effect has been increased in recent years.

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“…This cloud model has been applied to various engineering problems, such as the prediction of rock burst [37,38], the stability analysis of surrounding rock [39], the quality classification of rock masses, and the evaluation of the spontaneous combustion tendency of ore. This model has also been widely used in military fields and has achieved good results for power grid performance, agricultural production, water quality assessment, and other areas [40][41][42][43][44][45][46][47]. However, the cloud model exhibits deficiencies when addressing unilateral issues.…”

Section: Introductionmentioning

confidence: 99%

Application of an Improved Cloud Model and Distance Discrimination to Evaluate Slope Stability

Guo

Wang

Liu

2019

Mathematical Problems in Engineering

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With the rapid development of China's economy, the construction of infrastructure has continuously improved. In the past few years, the construction of water conservancy projects has been constantly developing, and related geological disasters have become increasingly prominent. The stability of water conservancy slopes is related to whether water conservancy projects can be safely constructed and built to function safely and effectively, which has become a topic of increasing concern for geologists and related researchers. This paper selects the Jinping 1 Hydropower Station in Sichuan, China, for analysis. Four categories of evaluation factors (geological, engineering, environmental, and monitoring) and 24 subfactors (17 quantitative indicators and 7 qualitative indicators) are selected to ascertain the risk of the slope more accurately. By investigating the deficiencies of the traditional cloud model, the related concepts and computational models of a finite-area cloud model are proposed. By obtaining the characteristic parameters, the degrees of membership of the measurement samples belonging to different risk levels are further obtained. The weights of the indicators determined by the cloud processor and the weighted distance discriminant method are used to determine the final weights and achieve a final classification of the slope stability level. The research results demonstrate that the weighted distance discriminant algorithm combined with the improved finite-interval cloud model can consider the comprehensive information of each evaluation index and the degrees of mutual influence between the indicators, making the evaluation results more objective. Moreover, the proposed approach can quickly and accurately classify slope stability and deliver a prediction of the safety, thereby providing new ideas for evaluating the stability of slopes.

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A cloud model based DNA genetic algorithm for numerical optimization problems

Cited by 55 publications

References 18 publications

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Nature inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments

Application of an Improved Cloud Model and Distance Discrimination to Evaluate Slope Stability

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