Problems and Countermeasures of Fruit and Vegetable Logistics Distribution Development in Guangxi Zhuang Autonomous Region

The logistics transportation and distribution of fruits and vegetables has become one of the important links for people to obtain food,and it is also an important direction and emerging challenge in the logistics industry.As the social economy and transportation develop,the consumption ability of residents has been improved,and the high demand for fruits and vegetables has promoted the transportation of fruits and vegetables to meet the development conditions of the future fruit and vegetable industry.The study of fruit and vegetable logistics distribution can improve the efficiency of fruit and vegetable distribution,improve the construction of fruit and vegetable distribution system,and also meet the needs of people for different kinds of fruits and vegetables.Taking Guangxi fruit and vegetable distribution as an example,through empirical investigation,this paper studies the existing problems in the development of logistics distribution in the fruit and vegetable distribution industry,and puts forward corresponding measures and countermeasures according to the problems,so as to innovate the fruit and vegetable distribution mode in Guangxi Zhuang Autonomous Region.

Themes and Challenges in Making Urban Freight Distribution Sustainable

The purpose of this article is to explore and classify themes and challenges in making urban freight distribution sustainable.The study has a cross sectional design which started by a narrative literature review and analysis of a sample of related literature(like peer-reviewed articles and EU(European Union)documents).It ended with complementary discussion and recommendation for tackling the challenges.The results of the study illustrate eight and seven emerged categories of themes and challenges,respectively.It is concluded that there is great need for a packet of mixed strategies as well as a more holistic perspective where all actors together analyse and design future set-ups and operation of urban freight distribution.Such a holistic view is essential in order to:understand how different actors of the chain look upon sustainable urban freight distribution,avoid sub-optimal policies/governing rules,and suggest close-to-reality solutions for tackling the challenges.Freight distribution in urban areas is the main focus of this article.In addition,the study is demarcated to eco/environmental aspect of sustainability although it is impossible to completely exclude its interaction with economic and social aspects.The results offered in this paper provide a systematic structure for classifying issues related to sustainable urban freight distribution;something which will be beneficial for managers and policy-makers when they approach sustainable supply chain management challenges.This study provides a synthesized classification of themes and challenges which can guide researchers,industries,authorities,and policy-makers in future sustainability efforts.

Research on the Best Routing Algorithm of Terminal Distribution Based on the Random Factor of Road Hustling Degree

Dijkstra algorithm is a basic algorithm to analyze the vehicle routing problem (VRP) in the terminal distribution of logistics center. According to the actual client demands of service speed and quality, the conceptions of economical distance of delivery and the best routing algorithm were given on the base of the Dijkstra algorithm with consideration of a coefficient of the road hustle degree. Economical distance of delivery is the shortest physical distance between two customers. It is the value of goods delivery in shortest distance when concerning factors such as the road length, the hustle degree, the driveway quantity, and the type of the road. The improved algorithm is being used in the development and application of a distribution path information system in the terminal distribution of logistics center. The simulation and practical case prove that the algorithm is effective and reasonable.

Research on Optimizing the Distribution Path of Agricultural Cold Chain Logistics in Green Consumption Era

In recent years, with the rapid development of China's fresh market, cold chain logistics ushered in a new development opportunity. Because of the late start and slow development of cold chain logistics in China, it is difficult to achieve cross-regional and offseason sales activities, resulting in a situation of high output and small sales volume, which is also an important reason for the high price and poor quality of fresh agricultural products. With the passage of time, the characteristics of cold chain distribution of agricultural products have become an important direction for the future development of logistics industry. In this paper, aiming at the characteristics of agricultural cold chain distribution, the carbon emissions in the process of distribution were quantified as costs and added to the total cost, and an optimization model of agricultural cold chain logistics path with time window considering the minimum total cost as the objective function was constructed. The improved genetic algorithm was used to solve the problem. The simulation results show that the improved genetic algorithm is an effective method to solve the optimization problem of agricultural cold-chain logistics path considering carbon emissions, and has guiding significance for the selection of low-carbon and environmentally friendly distribution routes for agricultural cold-chain logistics distribution enterprises.

S-curve networks and an approximate method for estimating degree distributions of complex networks

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol version 4） addresses, this paper proposes a forecasting model by using S curve （logistic curve）. The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions （i.e., Barabasi-Albert method） is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabasi-Albert method commonly used in current network research.

Application of Robust Strategies in Location Selection of Logistics Distribution Center for Fresh Agricultural Products

In view of the uncertainty in the location selection of logistics distribution center for the fresh agricultural products,the present study established a robust model based on the maximization of principal component score taking budget cost parameters as an example.In the process of model solving,the interval form of the uncertain set was used to clarify the constraint conditions,to transform into a certain 0-1 integer linear programming model,so as to solve with the aid of LINGO software.Finally,through studying the location selection of logistics distribution center for fresh agricultural products in the Beijing-Tianjin-Hebei region,it analyzed the application of the robust model and tested the validity of the model.

Study on Location of Wuhan Steel Logistics Distribution Center

This paper studies the location of Wuhan steel logistics distribution center. First of all, according to Wuhan Iron and Steel Plant sales in Hunan Province and the relative position of the city, the transport costs are calculated from Wuhan Iron and Steel Plant to the demand point. We further analyze the necessity of establishing steel logistics distribution center, using the precise center of gravity to determine the actual location of the distribution center. After the establishment of distribution center, the total freight is reduced by 15.46 million yuan from Wuhan Iron and Steel Plant to each city in Hunan province via distribution center each year. The results of this paper can provide theoretical basis for the logistics node planning of related enterprises.

Obtain the optimal of logistics delivery network with annealing algorithm

Simulated annealing(SA) algorithm is a heuristic algorithm,proposed one approximation algorithm of solving optimization combinatorial problems inspired by objects in the annealing process of heating crunch. The algorithm is superior to the traditional greedy algorithm,which avoids falling into local optimum and reaches global optimum. There are often some problems to find the shortest path,etc in the logistics and distribution network, and we need optimization for logistics and distribution path in order to achieve the shortest,best,most economical,and so on. The paper uses an example of SA algorithm validation to verify it,and the method is proved to be feasible.

Logistic Regression for Prediction and Diagnosis of Bacterial Regrowth in Water Distribution System

This paper focuses on the quantitative expression of bacterial regrowth in water distribution system. Considering public health risks of bacterial regrowth,the experiment was performed on a distribution system of selected area.Physical,chemical,and microbiological parameters such as turbidity,temperature,residual chlorine and pH were measured over a three-month period and correlation analysis was carried out.Combined with principal components analysis(PCA) ,a logistic regression model is developed to predict and diagnose bacterial regrowth and locate the zones with high risks of microbiology in the distribution system.The model gives the probability of bacterial regrowth with the number of heterotrophic plate counts as the binary response variable and three new principal components variables as the explanatory variables.The veracity of the logistic regression model was 90%,which meets the precision requirement of the model.

改进Theta^(*) 算法的物流无人机城域三维路径规划

针对物流无人机城域配送路径规划问题,使用改进栅格法进行环境建模,设计路径安全代价函数提高路径安全性。为了解决Theta^(*)算法在城市区域规划时路径海拔变化较大的问题,同时为减少路径节点数,提高路径平滑性,在算法实际代价函数中引入海拔变化代价及姿态调整代价;在算法搜索路径节点过程中,通过提出视线存在预设策略减少多余检查过程,提高算法搜索效率。与A*算法及Theta^(*)算法对比验证了改进Theta^(*)算法适用性。设计对照实验确定了目标函数权重及估价函数权重最优取值。在随机不同环境及真实环境下进行仿真,结果表明:相比于传统算法,改进Theta^(*)算法规划路径的海拔变化、路径点数、规划时间及路径总代价均有较明显减少,证明了改进策略的有效性,在城域无人机路径规划方面有一定应用价值。

Performance Appraisal Method of Logistic Distribution for Fresh Agricultural Products

Through the initial selection,screening and simplification,a set of performance appraisal system of logistic distribution suited to fresh agricultural products is established.In the process of establishing the appraisal indicator,the representative appraisal indicator of logistic distribution of fresh agricultural products is further obtained by delivering experts' survey and applying the ABC screening system.The distribution costs,transportation and service level belong to the first level indicator;packing fees,distribution processing fees,full-load ratio,haulage capacity,customer satisfaction and the strain capability of delivery personnel belong to second level indicator.At the same time,the weighing of each indicator is determined.The quantification is conducted on indicators.The qualitative indicators applies ten-point system and then coverts these indicators into percentage,that is the number between [0,1];as for the quantitative indicators,they are concluded to the interval [0,1] according to the actual value range of the indicators and by applying the grade of membership in the vague mathematics.Through the analyses of the advantages and disadvantages of the frequently used performance evaluation method and its applicable conditions,the comprehensive evaluation of logistic distribution of agricultural products obtained by using the method of fuzzy comprehensive appraisal.The results show that,in terms of reducing distribution costs,the packaging and distribution processing technology of fresh agricultural products should be improved,so as to reduce distribution costs.In the process of introducing the application of advanced technology,the high automatic logistic equipments should be introduced.

Importance of Generalized Logistic Distribution in Extreme Value Modeling

We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.

Modeling Patch Characteristics of Farmland Loss for Site Assessment in Urban Fringe of Beijing, China

Farmland protection and delimitation in the urban fringe considers not only natural factors but also the spatial characters and site factors. Taking Daxing District, Beijing in China as a case study, this paper used landscape ecology and power-law methods to analyze and evaluate farmland loss during the period of 2004-2007 based on the interpretation results of SPOT5 remote sensing images in 2004 and 2007. At the patch level, we selected four landscape indices, namely patch size, shape index, the nearest neighbor distance between farmland and construction land (including residential land and other construction land), and cropping type, to evaluate the risk of farmland loss and establish a farmland site analysis indicator system. The results showed that patch size and shape index have a significant positive correlation with farmland loss, whereas the distance to construction land has a clear negative correlation with farmland loss. As regards cropping type, fallow farmland is much easier for non-agricultural use than cultivated farmland. The relative transition ratio among vegetable land, fallow farmland and cultivated farmland is 1︰5.6︰1. The patch size of lost farmland follows a power-law distribution, indicating that not only small parcels but also large parcels can be lost. Patch size less than 4 ha or more than 15 ha is in high loss risk, between 4 ha and 10 ha in medium loss risk, and larger than 10 ha and less than 15 ha in low risk. Farmland with a more regular shape has a higher likelihood of loss. Patch shape index less than 2.0 is in high loss risk, between 2.0 and 3.0 in medium loss risk, and larger than 3.0 in low risk. Construction land has a varying impact on farmland loss, the residential land effected distance is 1000 m, and that of the other construction land is 2000 m. This analysis showed the relationships between site factors and farmland loss, and the analysis framework can provide support and reference for farmland protection and delimitation of prime farmland in China.

Estimation of scale parameters of logistic distribution by linear functions of sample quantiles

The large sample estimation of standard deviation of logistic distribution employs the asymptotically best linear unbiased estimators based on sample quantiles. The sample quantiles are established from a pair of single spacing. Finally, a table of the variances and efficiencies of the estimator for 5≤n≤65 is provided and comparison is made with other linear estimators.

Simulation Program to Determine Sample Size and Power for a Multiple Logistic Regression Model with Unspecified Covariate Distributions

Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including those that are heavily skewed to the left or right. Existing theoretical formulas, criteria, and simulation programs cannot accurately estimate the sample size and power of non-standard distributions. Therefore, we have developed a simulation program that uses Monte Carlo methods to estimate the exact power of a binary logistic regression model. This power calculation can be used for distributions of any shape and covariates of any type (continuous, ordinal, and nominal), and can account for nonlinear relationships between covariates and outcomes. For illustrative purposes, this simulation program is applied to real data obtained from a study on the influence of smoking on 90-day outcomes after acute atherothrombotic stroke. Our program is applicable to all effect sizes and makes it possible to apply various statistical methods, logistic regression and related simulations such as Bayesian inference with some modifications.

Forecasting the Rainfall Pattern on Upstream of Hirakud Reservoir Using L-Moment for Accessing the Inflow

Changes in the rainfall pattern are a challenge for filling schedule of reservoir, when it is fulfilling various demands. In monsoon fed reservoirs, the target remains for attaining full reservoir capacity in order to meet various demands during non-monsoon period and the flood control. The planners always eye towards the inflow trend and perspective frequency of rainfall in order to counter the extreme events. In this study, the case of Hirakud reservoir of Mahanadi basin of India is considered as this reservoir meets various demands as well as controls devastating floods. The inflow trend has been detected by using Mann Kendall test. The frequency analysis of monthly rainfall is calculated using L-moment program for finalizing a regional distribution. The falling trend in inflow to reservoir is visualized in the month of July and August. The Wakeby distribution is found suitable for the monthly rainfall of July, September and October, where as in June and August, General Extreme Value (GEV), General Normal (GN) and Pearson Type-III (PT-III) distributions are found suitable. The regional growth factors for the 20, 40, 50 and 100-year return period rain-falls along with inflow to reservoir observed between 1958-2010 are calculated in this study as a referral for reservoir operation policy.

On Finding Geodesic Equation of Two Parameters Logistic Distribution

In this paper, we used two different algorithms to solve some partial differential equations, where these equations originated from the well-known two parameters of logistic distributions. The first method was the classical one that involved solving a triply of partial differential equations. The second approach was the well-known Darboux Theory. We found that the geodesic equations are a pair of isotropic curves or minimal curves. As expected, the two methods reached the same result.

Inferences for the Generalized Logistic Distribution Based on Record Statistics

Estimation for the parameters of the generalized logistic distribution (GLD) is obtained based on record statistics from a Bayesian and non-Bayesian approach. The Bayes estimators cannot be obtained in explicit forms. So the Markov chain Monte Carlo (MCMC) algorithms are used for computing the Bayes estimates. Point estimation and confidence intervals based on maximum likelihood and the parametric bootstrap methods are proposed for estimating the unknown parameters. A numerical example has been analyzed for illustrative purposes. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

Securing color image transmission using compression-encryption model with dynamic key generator and efficient symmetric key distribution

There are a few issues related to the existing symmetric encryption models for color image data,such as the key generation and distribution problems.In this paper,we propose a compression-encryption model to solve these problems.This model consists of three processes.The first process is the dynamic symmetric key generation.The second one is the compression process,which is followed by encryption using keystreams and S-Boxes that are generated using a chaotic logistic map.The last process is the symmetric key distribution.The symmetric key is encrypted twice using Rivest-Shamir-Adleman(RSA)to provide both authentication and confidentiality.Then,it is inserted into the cipher image using the End of File(EoF)method.The evaluation shows that the symmetric key generator model can produce a random and dynamic symmetric key.Hence,the image data is safe from ciphertext-only attacks.This model is fast and able to withstand entropy attacks,statistical attacks,differential attacks,and brute-force attacks.