Logistic Distribution Research Articles

Review on Location of Fresh Cold Chain Logistics Distribution Center

This paper reviews the research status, existing problems and challenges, and future research directions of the location of fresh cold chain logistics distribution centers. The research background is based on factors such as the development of the fresh product market, the technological progress of cold chain logistics, the requirements of environmental protection and sustainable development, and the intensification of market competition. The significance of site selection includes improving transportation efficiency, reducing costs, improving customer satisfaction, optimizing supply chain networks, and achieving environmental sustainability.The former focuses on low-carbon, demand uncertainty, and competitive distribution center location, while the latter focuses on the new retail environment and cold chain distribution. The review of relevant literature points out that some progress has been made in the research, but there are challenges such as market demand uncertainty, incomplete data and limited model applicability.Future research directions include the location model of cold chain logistics distribution center based on big data, the location model considering sustainable development factors, and the location method of cold chain logistics distribution center integrating multi-index evaluation.In the conclusion, it is pointed out that in the past, the time window and the overall logistics network were rarely used as research evaluation indicators in the site selection problems, and the cost of reverse logistics and closed-loop supply chain was rarely considered. In the prospect part, it is proposed that in the future, we should pay attention to the problems of reverse logistics and closed-loop supply chain in the distribution of fresh agricultural products, consider the multi-objective optimization of low-carbon cold chain logistics network in different policies and fields, and combine full simulation technology and optimization technology to realize the system optimization research.

Fitting the return period of dengue fever epidemic in Guangdong province of China

ObjectivesThe prevention and control of dengue fever (DF) has been a major public health issue in Guangdong (GD) province, China. This study aims to analyze the return period (RP) and the return level (RL) of DF epidemic in GD, to help the formulation of prevention and control plan. MethodsThree models, namely Lognormal distribution (Lognor D.), normal distribution (Norm D.), and generalized logistic distribution (GLD) were selected to fit the annual number of indigenous DF cases in GD from 1978 to 2021. The coefficient of determination (R2), the root mean squared error (RMSE), and the Akaike information criterion (AIC) were used to evaluate the goodness of fit. We predicted the RP of 45130 historical maximum cases that occurred in 2014 and the RP of 4884 peak cases that occurred in 2019 over the 5 years up to 2021. ResultsFitting through the three models, the R2 was 0.98, 0.98, and 0.96, respectively. The predicted RLs of the annual DF case number were between 297 and 43234, 297 and 43233, 362 and 41868 for the RPs of 2–45 years. The predicted RPs of DF outbreaks exceeding the historical maximum were 43, 43, and 44 years, and the RPs of DF epidemic exceeding the peak in 2019 were 7, 7, and 8 years, respectively. Therefore, we predicted that GD would experience a DF outbreak beyond the historical maximum in the next 35 or 36 years from 2022. And in the next 4 or 5 years from 2022, there would be a DF epidemic exceeding the peak in 2019. ConclusionsThe study discloses a temporal periodicity inherent to the DF epidemic in GD. The three models are applicable for forecasting and evaluating the RP and RL of DF epidemic in GD, separately.

Indonesian disaster named entity recognition from multi source information using bidirectional LSTM (BiLSTM)

Precise logistic support is essential after a disaster occurs. It must be timely, accurate, targeted, and based on existing needs. However, obtaining sufficient and accurate information related to logistic distribution locations remains a key problem. Therefore, implementing Named Entity Recognition (NER) can address this issue. In recent years, news coverage through Indonesian digital news media and social media accounts has emerged as a promising source for building a disaster data corpus. This study implemented NER to extract and identify named entities from text-based information, particularly from Indonesian digital news media. In addition to using regular entities from the NER standard, this study introduced new entities specialized for disaster-related information, including DISASTER, SCALE, SUPPLIES, CASUALTIES, and OUTSIDE. The new disaster corpus in the Indonesian language for the NER model was obtained with an imbalanced dataset composition. To overcome this problem, random oversampling was applied. This study also utilized the BiLSTM model to recognize each entity in new textual information, evaluating its performance when the proposed Indonesian disaster corpus was used as a training reference in the deep learning model. Several optimization algorithms applied in BiLSTM were evaluated. The results showed improved BiLSTM performance using Adam optimization and a balanced corpus. Performance indicators achieved were 93.4 %, 82.4 %, and 87.5 % for precision, recall, and F1-score, respectively. The BiLSTM network captured long-range dependencies in sequential data provided by NER. Oversampling ensured that the proposed NER model could precisely recognize all entities and reduce biased results. Thus, the BiLSTM method can better identify entities in the textual corpus of Indonesian disaster-related online news.

Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm

Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm

Combining vehicle routing and bin packing problem for vehicle routing planning: A case study of a chemical factory

In the logistics distribution process, effective transportation management is required to ensure quality and timely delivery. In addition, transportation must be more economical and faster. The case study company is a chemical plant, an industrial company that produces products for hygiene and cleaning. The delivery manager plans the transportation routes based only on her experience because no decision-making aids are available. In addition, the manager considers the shipping order from first to last when arranging the products on the transportation vehicles. The goods for the final delivery location are placed at the back and bottom of the delivery truck. This cannot guarantee that the transportation routes set by the manager are suitable. Therefore, this study aims to plan delivery routes, arrange items in trucks, and reduce transportation costs for a case study of a chemical factory by using vehicle route problems and container filling problems. Then, the program is developed in Python using the Saving Algorithm, the 3D First Fit Decreasing Algorithm, and the 3D Best Fit Algorithm. The results show that the program method can reduce the use of transportation vehicles from 19 to 14, which is 26.32%; reduce the total distance from 5,499.8 kilometers to 3,406.92 kilometers, which is 38.05%; reduce the wages of transportation vehicles from 36,666 to 24,993 baht, which is 31.84%; can increase the average total weight per vehicle from 961.22 to 1,319.71 kilograms, which is 37.30%; and increase the average space utilization per vehicle from 37.93% to 51.47%, which is 13.54%. This method can reduce costs and increase efficiency for the company. Finally, the developed program also supports inexperienced operations managers in making decisions when planning transportation routes and loading goods, Thereby saving working time.

A method for exploring consumer satisfaction factors using online reviews: A study on anti-cold drugs

Anti-cold drugs prove effective in alleviating cold symptoms and minimizing complications. In recent years, there has been a growing tendency among the public to purchase these drugs online, driven by the prevalence of influenza. Maintaining a high level of consumer satisfaction is crucial for online pharmaceutical platforms. This study introduces a Multi-Attribute Decision Making (MADM) method to analyze online reviews from 31,392 consumers at JD Pharmacy. Unlike previous studies, multiple analytical tools are employed jointly to identify factors influencing consumer satisfaction. Four dosage forms of anti-cold drugs (granule, tablet, syrup, and spray) were analyzed using the Latent Dirichlet Allocation Model (LDA). Three tools (topic coherence curve, topic perplexity curve, and pyLDAvis visualization) were jointly applied. Then five satisfaction factors were identified as logistics distribution, drug efficacy, online consultation service, drug prices, and packaging quality. PROMETHEE II method was applied to rank the above factors. The results revealed variations in consumer satisfaction among different drug dosage forms. We conducted a detailed analysis of these distinctions. The results from this study will provide an effective reference to improve consumer satisfaction.

A STUDY ON THE LOCATION SELECTION OF LOGISTICS DISTRIBUTION CENTERS BASED ON E-COMMERCE

With the rapid development of e-commerce, the importance of logistics distribution center location selection is becoming increasingly prominent. In order to enhance the scientificity of logistics distribution center location selection, this paper systematically analyzes the main factors influencing location selection under the background of e-commerce, focusing on summarizing the methods and steps of location selection. Practice has proven that rational location selection can effectively improve logistics efficiency, reduce operating costs, and enhance competitiveness. In future development, enterprises should continue to focus on location selection issues, make optimal decisions based on their own development strategies and market environment.

Development of multidose thermotolerant formulations of a vector-based Covid-19 vaccine candidate, NDV-HXP-S in different product formats: Stability and preservative efficacy study

Current lead coronavirus vaccines require continuous cold or ultra-cold storage from the manufacturing site to the field to maintain protective efficacy. Since cold chain capacity is limited and complex, logistics planning is crucial to limit vaccine wastage.[1] The restrictive storage concerns also make it difficult to share vaccines between public health departments and neighboring states, leading to increased vaccine wastage.[2] A Newcastle Disease Virus (NDV) vector-based severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) vaccine candidate, NDV-HXP-S, offers a cost-effective alternative which aims to improve global access to SARS CoV-2 vaccines.[3] The NDV-HXP-S vaccine candidate can be mass-produced in chicken eggs and has demonstrated efficacy in preclinical studies, as well as acceptable safety andpotent immunogenicity in clinical studies.[3,4–10] To further advance the NDV-HXP-S vaccine candidate, this manuscript describes work focused on the development of multidose thermotolerant vaccine formulations (i.e., those which would not require continuous extendedrefrigeration), making it convenient to use and store, and simplifying transport and distribution logistics, especially in outbreak settings. Liquid and lyophilized formulations for parenteral administration were rigorously screened for the vaccine formulation’s ability to maintain S-antigen stability after exposure to temperaturestress at 40 °C, 25 °C, and 2 °C to 8 °C storage for six months. Preservative efficacy was evaluated to enable a multidose liquid vaccine format as well as endotoxin testing in lyophilized formulations. Lead liquid vaccine formations were identified that were able to maintain S-antigen content at 2 °C to 8 °C and 25 °C storage for the entire six-month study. Lead lyophilized vaccine formulations were identified which were able to maintain S-antigen content for six months at 2 °C to 8 °C, 25 °C, and 40 °C. Both the liquid and lyophilized formulations identified are improved thermotolerant SARS-CoV-2 vaccine formulations.

Optimization research on multi-trip distribution of reverse logistics terminal for automobile scrap parts under the background of sustainable development strategy

To effectively solve the reverse logistics distribution problem caused by the increasing number of scrapped parts in the automotive market, this study constructs a multi-trip green vehicle routing problem model with time windows by comprehensively considering the coordination between carbon dioxide emissions and cost efficiency. A hybrid adaptive genetic algorithm is proposed to solve this problem, featuring innovative improvements in the nearest neighbor rule based on minimum cost, adaptive strategies, bin packing algorithm based on the transfer-of-state equation, and large-scale neighborhood search. Additionally, to efficiently obtain location data for supplier factory sites in the distribution network, a coordinate extraction method based on image recognition technology is proposed. Finally, the scientific validity of this study is verified based on the actual case data, and the robust optimization ability of the algorithm is verified by numerical calculations of different examples. This research not only enriches the study of green vehicle routing problems but also provides valuable insights for the industry to achieve cost reduction, efficiency enhancement, and sustainable development in reverse logistics.

Meteorological Drought Analysis and Regional Frequency Analysis in the Kızılırmak Basin: Creating a Framework for Sustainable Water Resources Management

Drought research is needed to understand the complex nature of drought phenomena and to develop effective management and mitigation strategies accordingly. This study presents a comprehensive regional frequency analysis (RFA) of 12-month meteorological droughts in the Kızılırmak Basin of Turkey using the L-moments approach. For this purpose, monthly precipitation data from 1960 to 2020 obtained from 22 meteorological stations in the basin are used. In the drought analysis, the Standard Precipitation Index (SPI), Z-Score Index (ZSI), China-Z Index (CZI) and Modified China-Z Index (MCZI), which are widely used precipitation-based indices in the literature, are employed. Here, the main objectives of this study are (i) to determine homogeneous regions based on drought, (ii) to identify the best-fit regional frequency distributions, (iii) to estimate the maximum drought intensities for return periods ranging from 5 to 1000 years, and (iv) to obtain drought maps for the selected return periods. The homogeneity test results show that the basin consists of a single homogeneous region according to the drought indices considered here. The best-fit regional frequency distributions for the selected drought indices are identified using L-moment ratio diagrams and ZDIST goodness-of-fit tests. According to the results, the best-fit regional distributions are the Pearson-Type 3 (PE3) for the SPI and ZSI, generalized extreme value (GEV) for the CZI, and generalized logistic distribution (GLO) for the MCZI. The drought maps obtained here can be utilized as a useful tool for estimating the probability of drought at any location across the basin, even without enough data for hydrological research.

[89Zr]ZrCl4 for direct radiolabeling of DOTA-based precursors

IntroductionZirconium-89 (89Zr) is a positron emitter with several advantages over other shorter-lived positron emission tomography (PET) compatible radiometals such as gallium-68 or copper-64. These include practically unlimited availability, extremely low cost, greatly facilitated distribution logistics, positron energy fit for medical PET imaging, and sufficiently long physical half-life to enable PET imaging at later time points for patient-specific dosimetry estimations. Despite these apparent benefits, the reception of 89Zr in the nuclear medicine community has been tepid. The driving factor for the absence of broader adaptation is mostly routed in its final formulation — [89Zr]zirconium oxalate. While serving as a suitable precursor solution for the gold standard chelator deferoxamine (DFO), [89Zr]Zr-oxalate is inaccessible for the most commonly used chelators, such as the macrocyclic DOTA, due to its pre-chelated state.Consequently, pioneering work has been conducted by multiple research groups to create oxalate-free forms of [89Zr]Zr4+, either via chemical conversion of oxalate into other counterion forms or via direct radiochemical isolation of [89Zr]ZrCl4, showing that [89Zr]Zr-DOTA complexes are possible and stable. However, this success was accompanied by challenges, including complex and labor-intensive radiochemical processing and radiolabeling procedures as well as the relatively minuscule conversion rates. Here, we report on the direct production of [89Zr]ZrCl4 avoiding oxalate and metal contaminants to enable efficient radiolabeling of DOTA constructs. MethodsWe based our direct production of [89Zr]ZrCl4 on previously reported methods and further optimized its quality by including an additional iron-removing step using the TK400 Resin. Here, we avoided using oxalic acid and effectively minimized the content of trace metal contaminants. Our two-step purification procedure was automated, and we confirmed excellent radionuclide purity, minimal trace metals content, great reactivity over time, and high specific molar activity. In addition, DOTA-based PSMA-617 and DOTAGA-based PSMA-I&T were radiolabeled to demonstrate the feasibility of direct radiolabeling and to estimate the maximum apparent specific activities. Lastly, the biodistribution of [89Zr]Zr-PSMA-617 was assessed in mice bearing PC3-PIP xenografts, and the results were compared to the previously published data. ResultsA total of 18 batches, ranging from 6.9 to 20 GBq (186 to 541 mCi), were produced. The specific molar activity for [89Zr]ZrCl4 exceeded 0.96 GBq (26 mCi) per nanomole of zirconium. The radionuclidic purity was >99 %, and the trace metals content was in the <1 ppm range. The [89Zr]ZrCl4 remained in its reactive chemical form for at least five days when stored in cyclic olefin polymer (COP) vials. Batches of 11.1 GBq (300 mCi) of [89Zr]Zr-PSMA-617 and 14.4 GBq (390 mCi) of [89Zr]Zr-PSMA-I&T, corresponding to specific activities of 11.1 MBq/μg (0.3 mCi/μg), and 14.4 MBq/μg (0.39 mCi/μg), respectively, were produced. [89Zr]Zr-PSMA-617 animal PET imaging results were in agreement with the previously published data. ConclusionIn this work, we report on a suitable application of TK400 Resin to remove iron during [89Zr]ZrCl4 radiochemical isolation. The breakthrough allows for direct radiolabeling of DOTA-based constructs with [89Zr]ZrCl4, leading to high apparent molar activities and excellent conversion rates.

Challenges and Opportunities in Access to Essential Medicines in Rural Uganda

Access to essential medicines in rural Uganda is hindered by multifaceted challenges related to infrastructure, logistics, regulatory frameworks, and financial constraints. Poor road networks and inadequate transportation systems delay the delivery of medicines, while storage and supply chain management issues compromise medication quality and availability. Human resource shortages further impede distribution efforts, alongside financial limitations that affect procurement and sustainability. Regulatory reforms aimed at enhancing pharmacy practice have improved standards but pose implementation challenges. This review article employed a comprehensive literature review and analysis of existing research, policy documents, and case studies related to access to essential medicines in rural Uganda. Despite these obstacles, opportunities such as community-based interventions, technological innovations like mHealth, and public-private partnerships (PPPs) offer promising avenues to address these barriers. Strategic investments in infrastructure, regulatory compliance, and sustainable funding are crucial to improving access to essential medicines and healthcare outcomes in rural Uganda. Keywords: Essential Medicines Access, Rural Healthcare Challenges, Pharmacy Regulation Uganda, Medication Distribution Logistics, Public-Private Partnerships Healthcare

The Optimal Logistics Distribution Service Strategy of the E-commerce Closed-Loop Supply Chain Network under Blockchain Technology and the Government Blockchain Subsidy

The booming development of e-commerce has promoted the diversified development of logistics distribution services (LDS). For LDS, e-commerce retailers (e-retailers) often choose either the outsourced logistics distribution services strategy (OLDSS) or the self-built logistics distribution services strategy (SBLDSS). Although there are problems such as products getting lost and damaged during the logistics distribution process, the high transparency and traceability characteristics of blockchain technology (BT) can help solve the problem of products being lost and damaged in the logistics distribution process. However, due to the high cost of BT, e-retailers may encounter reduced sales, which causes the supply chain corporate profits to decrease. To encourage the BT investment enthusiasm of the e-retailers and regulate corporate profits, the government implements subsidies for e-retailers’ BT, namely, the government blockchain subsidy (GBS). In addition, in recent years, environmental degradation has become increasingly severe, causing negative impacts on people’s lives. To promote sustainable development, we use variational inequality to establish an e-commerce closed-loop supply chain (E-CLSC) network equilibrium model in which the network equilibrium decisions of e-retailers choosing the OLDSS and those choosing the SBLDSS are obtained. Then, we analyze the impact of the BT input cost and the GBS quota on equilibrium decisions by studying their properties and verifying the theoretical results by performing numerical examples. Finally, we analyze the profits of the e-retailers to obtain the impact of the BT input cost and the GBS quota on e-retailers’ choice of the optimal LDS strategy; in this way, we provide a scientific basis for e-retailers to choose the optimal LDS strategy. The results show that increasing the BT input costs reduces e-retailers’ product sales under the two LDS strategies, which decreases the production rate and the recovery rate of the products. When the BT input cost is low, SBLDSS is the best choice for e-retailers. When the BT input cost is high, OLDSS is the best choice for e-retailers. Moreover, there is a positive correlation between GBS and e-retailers’ product sales; thus, GBS is conducive to expanding market demand, regulating the profits of manufacturers, increasing the e-retailers’ profits, improving the enthusiasm of the e-retailers for BT investment, and promoting the overall development of supply chain enterprises. For e-retailers, choosing the OLDSS can lead to a better development of the E-CLSC.

Cold Chain Logistics and Joint Distribution: A Review of Fresh Logistics Modes

With the continuous development of the global logistics industry, cold chain transportation and joint distribution, as critical strategies in supply chain management, are gradually becoming key means to ensure the safe transportation of perishable goods, pharmaceuticals, and other temperature-sensitive commodities. The present study is dedicated to an in-depth exploration of cold chain logistics and joint distribution, with a particular focus on a review of fresh food logistics modes, aiming to comprehensively understand their operational modes, advantages, challenges, and future development trends. The present study elucidates the basic concepts of fresh food logistics and underscores its significance in supply chain management. Through comparative analysis of different operational modes, it reveals their advantages in enhancing efficiency, reducing costs, and mitigating environmental impacts. The present study focuses on the operational mode of joint distribution, discussing its application in cold chain logistics and its differences from traditional logistics modes. Through case studies and empirical analysis, it evaluates the impact of joint distribution on logistics efficiency and costs, as well as its potential to enhance transportation efficiency and reduce carbon emissions. Lastly, the present study provides an outlook on the future development trends of cold chain logistics and joint distribution, discussing the influences of technological innovation, policy support, and industry collaboration and offering recommendations and prospects to drive the sustained development of the industry. Through a comprehensive summary of fresh food logistics, cold chain logistics operational modes, and joint distribution operational modes, this paper aims to provide in-depth theoretical support and practical guidance for related research and practices.

Optimization of cold chain logistics distribution paths for community buying considering cost and time window: The case of J Center

AbstractIn recent years, the community group buying market has been developing rapidly, and the group buying categories are mainly fresh food, so one of the keys to the success of the community group buying platform lies in the supply chain logistics, in which the cold chain logistics is the key to guarantee the fresh food products for the time and quality. In this paper, on the combing research of the theories and problems of community group purchase, cold chain logistics, and vehicle path planning, in view of the existing problems of cold chain logistics and distribution business in Jinan distribution center of J company's community group purchase, taking into account the actual demand of the grid station and the characteristics of the fresh products to be stored at low temperatures, we constructed the optimization model of the cold chain logistics and distribution path that minimizes the total cost under the demand of the fuzzy time window of the grid station, and designed the distribution area is divided by using K‐means clustering, and then, the distribution path in each sub‐distribution area is optimized and solved by genetic algorithm, and then, the validity of the optimization scheme is verified, the number of distribution trucks used is reduced by two, and the distribution cost is reduced by 12.77%, and optimization measures such as promoting the standardization of warehousing and distribution, and creating a digital and integrated logistics information platform are proposed.

Application of EIQ-ABC Analysis Method in Warehouse Management of X Cold Chain Logistics Distribution Center

Application of EIQ-ABC Analysis Method in Warehouse Management of X Cold Chain Logistics Distribution Center

Inferences on stress-strength reliability $$R=\text{ P }[Y&lt;X&lt;Z]$$ for progressively type-II censored Weibull half logistic distribution

Inferences on stress-strength reliability $$R=\text{ P }[Y&lt;X&lt;Z]$$ for progressively type-II censored Weibull half logistic distribution

Impact of Individual Budgets on Work and Financial Well-Being of Supported Employment Recipients With Serious Mental Illness.

The authors sought to determine whether providing recipients of supported employment with individual budgets from which they could purchase employment-related goods and services would improve employment and financial outcomes. Sixty study participants were recruited from an individual placement and support (IPS) program and randomly assigned (1:1) to receive IPS services only (N=32) or IPS services with a 12-month $950 flexible fund called a career account (N=28). Participants receiving IPS and a career account met with staff who helped them identify employment goals and create a budget for purchases directly tied to these goals. The primary outcome was competitive employment; secondary outcomes included job tenure, days worked, total earnings, and financial well-being. Outcomes were analyzed by using adjusted generalized linear models (GLMs) with binary logistic, negative binomial, and linear distributions. The proportion of participants who achieved competitive employment was largely similar for those in the career account+IPS group (54%) and in the IPS-only group (47%). However, the GLM analysis revealed that career account+IPS participants had significantly longer job tenure, more total days of employment, and higher total earnings than IPS-only participants. Feelings of financial well-being increased significantly among career account participants, whereas financial well-being declined among control participants. The amount of career account dollars participants spent was positively and significantly associated with longer job tenure, more days employed, and higher total earnings. Combining flexible funds with IPS-supported employment achieved some superior outcomes compared with IPS only. Further research is needed to assess the longer-term effects of this practice and its cost-effectiveness.

Logistic Nadarajah-Haghighi distribution: Estimation and properties

Logistic Nadarajah-Haghighi distribution: Estimation and properties

Comparação das distribuições Normal, Logística, Laplace e t de Student para o erro experimental na descrição bayesiana do acúmulo de matéria seca de Allium sativum

ABSTRACT: This study assessed distributions associated with Bayesian nonlinear modeling error in the description of total plant dry matteraccumulation (TDMA) of Allium sativumas a function of days after planting (DAP). According to the DIC criterion, Logistic and Gompertzmodels that use student’s t distribution error exhibited the highest DIC with logistic error distribution. In general, the difference of DIC in all the scenarios was not more than 5.The Bayes factor (BF) criterion showed no difference in the Logistic and Gompertzmodel fit when four distributions are used for the errors, where BF values do not exceed 2. Posterior distributions and the usual estimators of Logistic and Gompertz model parameters were similar even forvaried error distribution. In summary, there was no difference in the use of 4 distributions associated with the modeling error of garlic plant growth by the Bayes factor, whereby the results showed that alternating between error distributions significantly changes the number of Markov Chain Monte Carlo (MCMC) iterations.