Multi-product budget-constrained acquistion and pricing with uncertain demand and supplier quantity discounts

We consider the joint acquisition and pricing problem where the retailer sells multiple products with uncertain demands and the suppliers provide all unit quantity discounts.The problem is to determine the optimal acquisition quantities and selling prices so as to maximize the retailer’s expected profit, subject to a budget constraint. This is the first extension to consider supplier discounts in the constrained multi-product newsvendor pricing problem. We establish a mixed integer nonlinear programming (MINLP) model to formulate the problem, and developaLagrangian based solution approach.Computational results for the test problems involving up to thousand products are reported, which show that the Lagrangian based approach can obtain high-quality solutions in a very short time

Optimal production planning for a multi-product closed loop system with uncertain demand and return

We study the production planning problem for a multi-product closed loop system, in which the manufacturer has two channels for supplying products: producing brand-new products and remanufacturing returns into as-new ones. In the remanufacturing process, used products are bought back and remanufactured into as-new products which are sold together with the brand-new ones. The demands for all the products are uncertain, and their returns are uncertain and price-sensitive. The problem is to maximize the manufacturer\u27s expected profit by jointly determining the production quantities of brand-new products, the quantities of remanufactured products and the acquisition prices of the used products, subject to a capacity constraint. A mathematical model is presented to formulate the problem and a Lagrangian relaxation based approach is developed to solve the problem. Numerical examples are presented to illustrate the model and test the solution approach. Computational results show that the proposed approach is highly promising for solving the problems. The sensitivity analysis is also conducted to generate managerial insights

Enhancing Customer Satisfaction Analysis with a Machine Learning Approach: From a Perspective of Matching Customer Comment and Agent Note

With the booming of UGCs, customer comments are widely utilized in analyzing customer satisfaction. However, due to the characteristics of emotional expression, ambiguous semantics and short text, sentiment analysis with customer comments is easily biased and risky. This paper introduces another important UGC, i.e., agent notes, which not only effectively complements customer comment, but delivers professional details, which may enhance customer satisfaction analysis. Moreover, detecting the mismatch on aspects between these two UGCs may further help gain in-depth customer insights. This paper proposes a machine learning based matching analysis approach, namely CAMP, by which not only the semantics and sentiment in customer comments and agent notes can be sufficiently and comprehensively investigated, but the granular and fine-grained aspects could be detected. The CAMP approach can provide practical guidance for following-up service, and the automation can help speed-up service response, which essentially improves customer satisfaction and retains customer loyalty

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time

Circuit Breaker Fault Diagnosis Method Based on Improved One-Dimensional Convolutional Neural Network

Aiming at the problems of manual feature extraction and poor generalization ability of model in traditional circuit breaker fault diagnosis technology, a circuit breaker fault diagnosis method based on improved one-dimensional convolutional neural network is proposed. Firstly, the input feature sequence is adaptively weighted by self-attention mechanism to highlight the weight of important information; Secondly, 1 1 convolution layer and global average pooling layer are used to replace the full connection layer, which reduces the model training parameters, improves the training efficiency and prevents the phenomenon of over-fitting. Aiming at the problem of small number of data samples, the data is enhanced by Generative Adversarial Network. After adding the generated data to the original data, the accuracy of fault identification is further improved. The experimental results show that this method can effectively and accurately identify different fault types of circuit breaker, and verify the feasibility of its engineering application

Application of evolution-based uncertainty design on gear

The evolution of mechanical parameters, a factor affecting the mechanical reliability, has gathered more attention nowadays. However, studies on time varying uncertainty can hardly be found. A new method based on evolution-based uncertainty design (EBUD) is applied to the design of gear in this paper. Considering the wear evolution over the lifetime, a tooth wear’s time-varying uncertainty model based on the continuous-time model and Ito lemma is established. Drift and volatility functions dependent on the drift rate and volatility rate of rotational speed and torque are used to express the time-varying uncertainty of tooth thickness. The method can predict the reliability and provide an instruction in reliability improving, maintenance and repair of the gear system

Clinical, radiological, and laboratory features of HIV-negative pulmonary cryptococcosis with regard to serum lateral flow assay

IntroductionCryptococcosis is the second most common invasive yeast infection in China. Pulmonary cryptococcosis (PC) is difficult to diagnose due to the lack of specific clinical features and the limitation of diagnostic techniques. Although lateral flow assay was very useful in diagnosing cryptococcal infection, quite a few patients with PC presented negative serum lateral flow assay (sLFA).MethodsWe conducted a retrospective study of HIV-negative patients who were diagnosed with PC in our hospital over the past decade to explore the potential relationship between the clinical profiles and sLFA in PC.ResultsIn total, 112 patients with sLFA tested were enrolled in this study, of which 58.93% were male. The positivity rate of sLFA for PC was 91.07%. The extent of pulmonary lesions was positively correlated with sLFA grade (Spearman r = 0.268, p < 0.01). Solitary nodule (SN) and pneumonia were the most common imaging findings in PC with negative and positive sLFA respectively. Among 65 symptomatic PC patients, 14 presented with fever and had higher hypersensitive C-reactive protein (hsCRP) level and more extensive pulmonary involvement (Mann-Whitney U test, p < 0.05) than those without fever. Symptomatic PC patients were more likely to have positive results of sLFA (Mann-Whitney U test, p = 0.05) compared against asymptomatic ones.DiscussionIn conclusion, negative sLFA cannot exclude PC in patients with a solitary nodule in lung. Positive sLFA is more reliable in diagnosing PC in symptomatic patients with diffused lesions in lung who generally experience a more severe systemic inflammatory reaction