Analysis and Optimal Design of a WPT Coupler for Underwater Vehicles Using Non-Dominated Sorting Genetic Algorithm

Liang, Bo; Mao, Zhaoyong; Zhang, Kehan; Liu, Peizhou

doi:10.3390/app12042015

Cited by 11 publications

(9 citation statements)

References 21 publications

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“…The output of fresh agricultural products every year is quite amazing, and freezing technology is still in continuous research and breakthroughs, so the development space of this type of food is quite huge. Through the review of relevant information, it is known that there are about 400 million tons of such products flowing into the market every year in China, and the “2015-China Cold Chain Logistics Development Report” also pointed out that, by the end of 2014, the total revenue of China's cold chain logistics has reached 3.74 trillion yuan, the total demand is 104.88 million tons, the growth rate is 18%, and the most important thing is that it has exceeded 15% for 3 consecutive years [ 2 ]. Distribution of cold chain logistics is one of the important problems that need to be solved urgently.…”

Section: Introductionmentioning

confidence: 99%

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

Zhang¹

2022

Computational Intelligence and Neuroscience

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The products of the enterprise are the logistics objects of the enterprise. Therefore, the company’s products are the primary factor affecting logistics costs. The products of different enterprises may be different in terms of the type, nature, volume, quality, and physical and chemical properties of the products, which will have different impacts on the cost of logistics activities such as warehousing, transportation, and material handling of enterprises. More and more enterprises have taken the cost of logistics distribution as one of the important indicators affecting the development of enterprises; especially, cold chain logistics has been rapidly developed and valued in recent years, because the requirements of such products for delivery time, distribution efficiency, and distribution environment are very strict, whether the goods can be distributed in a standard and reasonable environment and whether the delivery vehicle can deliver the goods within the time specified by the customer have greatly affected the safety of frozen and refrigerated food. Therefore, this paper reduces the cost of the distributor through the optimization of the distribution path of cold chain logistics and makes the goods distributed can be delivered to the customer faster and more reasonably by establishing an integrated optimization platform, which is of great significance for how to reduce the cost of enterprises. Therefore, this paper starts from the function with the lowest distribution cost as the goal, comprehensively considers the specific characteristics of cold chain logistics, given the relevant constraints, uses the improved genetic algorithm to iterate on the given scheme, sends the improved new scheme to the simulation software for simulation operation, then sends the results obtained by the operation to the genetic algorithm for the next iteration, and repeats it in turn until the prespecified conditions can be terminated. Therefore, this paper summarizes some problems and development status in cold chain logistics and distribution routes by consulting relevant literature, optimizes the scheme by using VRP model combined with constraints, establishes a distribution system model, and finally verifies and analyzes to obtain a more reasonable and satisfactory solution. The innovation of this paper is that the research on the VRP problem is optimized through an improved genetic algorithm, certain improvements have been made in the coding method and the operation of selection, crossover, variation, etc., and the improved genetic algorithm can greatly reduce the number of program iterations. Then, we use the integrated optimization platform to import the solution into FlexSim for simulation, each simulation of the new solution will be transmitted to MATLAB through the Excel table for the next optimization iteration, and we repeat the above steps until the preset conditions are met after the termination. This would lead to a more realistic and satisfactory solution.

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Section: Introductionmentioning

confidence: 99%

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

Zhang¹

2022

Computational Intelligence and Neuroscience

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“…2) Genetic Algorithm (GA): GA is proposed by Professor J. Holland of the United States in 1975. Its main feature is the direct operation of the structure of the object; there is no limit of derivation and continuity of the function; it has better global optimization ability [14]. GA is a computational model for simulating the natural selection and genetic mechanism of Darwin's theory of biological evolution.…”

Section: B Svm Parameter Optimiztion Methods 1) Random Selectionmentioning

confidence: 99%

Application of Optimized SVM in Sample Classification

Yao

2022

IJACSA

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Support vector machines (SVM) have unique advantages in solving problems with small samples, nonlinearity and high dimension. It has a relatively complete theory and has been widely used in various fields. The classification accuracy and generalization ability of SVMs are determined by the selected parameters, for which there is no solid theoretical guidance. To address this parameter optimization problem, we applied random selection, genetic algorithms (GA), particle swarm optimization (PSO) and K-fold cross validation (k-CV) method to optimize the parameters of SVMs. Taking the classification accuracy, mean squared error and squared correlation coefficient as the goal, the K-fold cross validation method is chosen as the best way to optimize SVM parameters. In order to further verify the best performance of the SVM whose parameters are optimized by the K-fold cross validation method, the back propagation neural network and decision tree are used as the contrast models. The experimental results show that the SVM-cross validation method has the highest classification accuracy in SVM parameter selection, which lead to SVM classifiers that outperform both BP neural networks and decision tree method.

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“…Algorithms like the genetic algorithm (GA) and sequential quadratic programming (SQP) are commonly applied in underwater IPT optimization issues, for they have the advantages of fast searching speed and accurate results [27]. Furthermore, improved algorithms based on conventional ones are also widely applied [36]. The MISQP optimization algorithm is based on the improved SQP algorithm by the gradient method, which can be used in both response surface optimization and direct optimization problems.…”

Section: Parameter Optimization Principlesmentioning

confidence: 99%

Design of a Highly Compatible Underwater Wireless Power Transfer Station for Seafloor Observation Equipment

Cai

Lyu

Wang

et al. 2023

JMSE

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Conventional cabled seafloor observatories (CSOs) power in-situ instruments via wet-mated or dry-mated direct electrical contact (DEC) connectors to achieve long-term and real-time observation. However, the DEC connectors have high risks of water leakage and short circuits in power feeding, especially under high water pressure. This paper proposes a highly compatible underwater station based on inductive wireless power transfer (IPT) technology to address the above reliability issue. A novel energy transmitter with runway-structure coils is applied to the proposed underwater station to cover a sufficient power feeding area so that various in-situ equipment can be powered with desirable misalignment tolerance. The magnetic field distribution is analyzed by both derivation and finite element analysis (FEA) methods, and the principal parameters of the transmitter are further optimized and compared with both the mixed-integer sequential quadratic programming (MISQP) algorithm and the evolutionary algorithm (EA) for better performance. The same results show a reliable optimization process. The WPT circuit characteristics are also investigated to power different loads and improve the power transmission efficiency. The output power decreases, and the transmission efficiency rises and then decreases as the load increases. In addition, receivers with higher mutual inductance have better transmission performance. A prototype of the underwater station has been tested both in air and in water, and the experimental results have proven it can power multiple seafloor observation instruments stably and achieve compatibility requirements. The maximum output power of the station prototype for testing is 100 W, and the maximum overall transmission efficiency is 61%.

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Analysis and Optimal Design of a WPT Coupler for Underwater Vehicles Using Non-Dominated Sorting Genetic Algorithm

Cited by 11 publications

References 21 publications

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm

Application of Optimized SVM in Sample Classification

Design of a Highly Compatible Underwater Wireless Power Transfer Station for Seafloor Observation Equipment

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