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.

Exploring Hybrid Genetic Algorithm Based Large-Scale Logistics Distribution for BBG Supermarket

In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket.We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm.Greedy algorithm is applied to initialize the population,and then hill-climbing algorithm is used to optimize individuals in each generation after selection,crossover and mutation.Our approach is evaluated on the dataset of BBG Supermarket which is one of the top 10 supermarkets in China.Experimental results show that our method outperforms some other methods in the field.

Selection of logistics distribution center location for SDN enterprises

The location selection of the logistics distribution center for a supply and demand network(SDN)enterprises directly affected the efficiency of the logistics system operation and the customer service level.In this paper,we present a location selection model of the logistics distribution center for SDN enterprises.In order to improve the optimization effectiveness of the traditional methods in solving the location selection problem,an improved firefly algorithm was presented.By introducing a coordination factor,the search step can be automatically adjusted,and the accuracy of the algorithm can be improved.By introducing a chaotic search strategy,the diversity of firefly populations and the global optimization ability of the algorithm can be improved.The simulation experiments showed that the improved firefly algorithm achieved a more favorable effectiveness than three other algorithms we tested.

Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.

Research on Mobile-Based Logistics Information System for Hainan Agricultural Products

The current situation,information technology and problems of logistics for agricultural products were summarized.Some key technologies involved in mobilebased logistics information system for Hainan agricultural products were analyzed,such as information classification and retrieval,user information authentication via QR code,and logistics information services based on WEB and mobile devices.Emphasis was given to study the design idea,content,method for the system.

Study on the Self-supporting Logistics Mode based on B2C E-commerce Enterprises

Taking B2C E-commerce enterprises as the center, it can be divided into a set of logistics activities upstream supply chain logistics producer to B2C e-commerce enterprises, and the B2C e-commerce enterprise logistics to client consumer, and the paper focuses on the study of self-supporting logistics for the E-commerce enterprise. According to the development status of current B2C electronic commerce enterprise in our country and logistics, the paper study B2C electric business enterprise how to correctly choose the logistics mode and how to promote the business logistics operation level.

Research on the key technology of RFID and its application in modem logistics

The paper study communication protocol, the structure of the circuit, antenna design of radio frequency identification technology （RFID）, and puts forward a scheme based on IOT application： RFID logistics tracking system. Finally, the paper study the logistics distribution center information management model from three aspects of the system design objectives, system function analysis and system architecture design based on RFID.

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.

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.

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.

Gumbel-Exponentiated Weibull {Logistic} Lifetime Distribution and Its Applications

A new generalized exponentiated Weibull model called Gumbel-exponentiated Weibull {Logistic} distribution is introduced and studied. The new distribution extends the exponentiated Weibull distribution with additional parameters and bimodal densities. Some new and earlier distributions formed the sub-models of the proposed distribution. The mathematical properties of the new distribution including expressions for the hazard function, survival function, moments, order statistics, mean deviation and absolute mean deviation from the mean, and entropy were derived. Monte Carlo simulation study was carried out to assess the finite sample behavior of the parameter estimates by maximum likelihood estimation approach. The superiority of the new generalized exponentiated Weibull distribution over some competing distributions was proved empirically using the fitted results from three real life datasets.

A Storm Surge Intensity Classification Based on Extreme Water Level and Concomitant Wave Height

Storm surge is one of the predominant natural threats to coastal communities. Qingdao is located on the southern coast of the Shandong Peninsula in China. The storm surge disaster in Qingdao depends on various influencing factors such as the intensity, duration, and route of the passing typhoon, and thus a comprehensive understanding of natural coastal hazards is essential. In order to make up the defects of merely using the warning water level, this paper presents two statistical distribution models(Poisson Bi- variable Gumbel Logistic Distribution and Poisson Bi-variable Log-normal Distribution) to classify the intensity of storm surge. We emphasize the joint return period of typhoon-induced water levels and wave heights measured in the coastal area of Qingdao since 1949. The present study establishes a new criterion to classify the intensity grade of catastrophic storms using the typhoon surge estimated by the two models. A case study demonstrates that the new criterion is well defined in terms of probability concept, is easy to implement, and fits well the calculation of storm surge intensity. The procedures with the proposed statistical models would be useful for the disaster mitigation in other coastal areas influenced by typhoons.

Nearly best linear estimates of logistic parameters based on complete ordered statistics

Deals with the determination of the nearly best linear estimates of location and scale parameters of a logistic population, when both parameters are unknown, by introducing Blom’s semi empirical ’α,β correction’ into the asymptotic mean and covariance formulae with complete and ordered samples taken into consideration and various nearly best linear estimates established and points out the high efficiency of these estimators relative to the best linear unbiased estimators (BLUEs) and other linear estimators makes them useful in practice.

Study of Vertical Breakwater Reliability Based on Copulas

The reliability of a vertical breakwater is calculated using direct integration methods based on joint density functions.The horizontal and uplifting wave forces on the vertical breakwater can be well fitted by the lognormal and the Gumbel distributions,respectively.The joint distribution of the horizontal and uplifting wave forces is analyzed using different probabilistic distributions,including the bivariate logistic Gumbel distribution,the bivariate lognormal distribution,and three bivariate Archimedean copulas functions constructed with different marginal distributions simultaneously.We use the fully nested copulas to construct multivariate distributions taking into account related variables.Different goodness fitting tests are carried out to determine the best bivariate copula model for wave forces on a vertical breakwater.We show that a bivariate model constructed by Frank copula gives the best reliability analysis,using marginal distributions of Gumbel and lognormal to account for uplifting pressure and horizontal wave force on a vertical breakwater,respectively.The results show that failure probability of the vertical breakwater calculated by multivariate density function is comparable to those by the Joint Committee on Structural Safety methods.As copulas are suitable for constructing a bivariate or multivariate joint distribution,they have great potential in reliability analysis for other coastal structures.

Collapsibility of odds ratios for a continuous outcome variable

The sign of an association measure between two varibles may be strongly affected and even be reversed after marginalization over a backgruoud variable, which is the well-known Yule-Simpson paradox.Odds ratios are strongly collapsible over a background variable if they remain unchanged no matter how the background variable is partially pooled.In this paper, we firstly give some definitions and notations about odds ratios between a dichotomous explanatory variable and a continuous response variable.Then, we present conditions for simple collapsibility of odds ratios.Further, necessary and sufficient conditions are given for strong collapsibility of odds ratios for continuous outcome variable.

Study on Inventory Cost Control under JIT System

Traditional inventory control methods generally emphasize minimizing costs. Under current thinking, we not only consider cost control, but also tie inventory management directly into production scheduling. This system, called ＂Just-in-Time delivery＂, is based on having inventory arrive at the factory door just as it is needed on the assembly line. This inventory management technique of essential zero raw material inventory speeds inventory turnover rate and greatly reduces holding cost. This paper analyzes and compares all aspects related to both traditional and JIT systems, and explores ways of reducing inventory costs. The result is the elimination of waste, the speed-up of inventory turnover and the increase in productivity, all with the objective of maximizing profitability. Using advanced logistics （physical distribution methods） will enhance the business image, strengthen international competitive ability and contribute greatly to increase gross domestic product.

Lean Construction in Supply Chain Management： Supplier and Buyer Relationship in Social Housing

To the accomplishment of this article, we have chosen, as a case study, a small Goiana construction company that acted in the market of social housing. The main goal of this work is to analyze the fundamental aspects related to the management of the flow of supplies in civil construction to achieve a greater streamlining of logistic processes involved in supplying material. A checklist was developed for the purpose of data collection, and it was applied by means of an interview with the person in charge of the purchase department of the enterprise. In addition, this person is the engineer of the site. Taking into account the exploratory feature of this research, the construction site was visited so that some issues, such as quality aspects, losses, cleanliness and organization, could be observed. This on-site data collection visit was carried out through visual analyses and photographs. The obtained results were subdivided into a quantitative and a qualitative analysis. In this way, it was possible to see that the production process still has many phases to be improved. What is more, it was possible to see that the construction company knows its flaws and necessities to improve its processes although the final result does not have the expected quality. Being aware of this need for improvement, the construction company aims at having an affordable price product to the target public, especially when it is associated to an image that shows quality.

Symbol RFID Technology to be Deployed at United States Defense Logistics Agency's Distribution Centers Worldwide

Symbol Technologies, Inc., The Enterprise Mobility Company, today announced that it had been selected by ODIN technologies, the leader in the physics of RFID testing, software and deployment, to support its recent contract win with the United States Defense Logistics Agency (DLA), the United States Department of Defense’s (DoD) logistics combat support agency that provides supplies and services to America’s military forces worldwide.

A parsimonious Bayesian predictive model for forecasting new reported cases of West Nile disease

Upon researching predictive models related toWest Nile virus disease,it is discovered that there are numerous parameters and extensive information in most models,thus contributing to unnecessary complexity.Another challenge frequently encountered is the lead time,which refers to the period for which predictions are made and often is too short.This paper addresses these issues by introducing a parsimonious method based on ICC curves,offering a logistic distribution model derived from the vector-borne SEIR model.Unlike existing models relying on diverse environmental data,our approach exclusively utilizes historical and present infected human cases(number of new cases).With a yearlong lead time,the predictions extend throughout the 12 months,gaining precision as new data emerge.Theoretical conditions are derived to minimize Bayesian loss,enhancing predictive precision.We construct a Bayesian forecasting probability density function using carefully selected prior distributions.Applying these functions,we predict monthspecific infections nationwide,rigorously evaluating accuracy with probabilistic metrics.Additionally,HPD credible intervals at 90%,95%,and 99%levels is performed.Precision assessment is conducted for HPD intervals,measuring the proportion of intervals that does not include actual reported cases for 2020e2022.

Medical image denoising using simple form of MMSE estimation in Poisson-Gaussian noise model

Poisson-Gaussian noise is the basis of image formation for a great number of imaging systems used in variety of applications, including medical and astronomical imaging. In wavelet domain, the application of Bayesian estimation method with generalized Anscombe transform in Poisson-Gaussian noise reduction algorithm has shown remark- able success over the last decade. The generalized Anscombe transform is exerted to convert the Poisson-Gaussian noise into an additive white Gaussian noise （AWGN）. So, the resulting data can be denoised with any algorithm designed for the removal of AWGN. Here, we present simple form of minimum mean square error （MMSE） estimator for logistic distribution in Poisson-Gaussian noise. The experimental results show that the proposed method yields good denoising results.