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.

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.

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.

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.

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.

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.

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.

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.