Recent trends in modeling of deteriorating inventory

4. Modelling Survival Data in Medical Research

This paper presents a complete and up-to-date survey of published inventory literature for the deteriorating (decaying) inventory models. More specifically, those papers are addressed that consider the effect of deterioration as a function of the on-hand level of inventory. The basic features, extensions and generalization of various models are discussed. A classification scheme is presented along with suggestions for future research.

https://link.springer.com/content/pdf/10.1057%2Fjors.1991.4.pdf

Survey of Literature on Continuously Deteriorating Inventory Models

Infertility and problems of impaired fecundity have been a concern through ages and is also a significant clinical problem today, which affects 8-12% of couples worldwide. Of all infertility cases, approximately 40-50% is due to "male factor" infertility and as many as 2% of all men will exhibit suboptimal sperm parameters. It may be one or a combination of low sperm concentration, poor sperm motility, or abnormal morphology. The rates of infertility in less industrialized nations are markedly higher and infectious diseases are responsible for a greater proportion of infertility. The present literature will help in knowing the trends of male factor infertility in developing nations like India and to find out in future, various factors that may be responsible for male infertility.

Trends of male factor infertility, an important cause of infertility: A review of literature.

Approximately 10 to 15% of couples are impacted by infertility. Recently, the pivotal role that lifestyle factors play in the development of infertility has generated a considerable amount of interest. Lifestyle factors are the modifiable habits and ways of life that can greatly influence overall health and well-being, including fertility. Many lifestyle factors such as the age at which to start a family, nutrition, weight, exercise, psychological stress, environmental and occupational exposures, and others can have substantial effects on fertility; lifestyle factors such as cigarette smoking, illicit drug use, and alcohol and caffeine consumption can negatively influence fertility while others such as preventative care may be beneficial. The present literature review encompasses multiple lifestyle factors and places infertility in context for the couple by focusing on both males and females; it aims to identify the roles that lifestyle factors play in determining reproductive status. The growing interest and amount of research in this field have made it evident that lifestyle factors have a significant impact on fertility.

/pdf/lifestyle-factors-and-reproductive-health-taking-control-of-ob45s39pgz.pdf

Lifestyle factors and reproductive health: taking control of your fertility

In this chapter, we review the theory of optimum regression designs. Concept of continuous design and different optimality criteria are introduced. The role of de la Garza phenomenon and Loewner order domination are discussed. Equivalence theorems for different optimality criteria, which play an important role in checking the optimality of a given otherwise prospective design, are presented. These results are repeatedly used in later chapters in the search for optimal mixture designs. We present standard optimality results for single variable polynomial regression model and multivariate linear and quadratic regression model . Kronecker product representation of the model(s) and related optimality results are also discussed.

Optimal Regression Designs

The paper studies an inventory model for deteriorating items under permissible delay in payment and stochastic inflation conditions. The deteriorating rate is assumed to be constant and the demand for the item is dependent on its selling price. A periodic review policy has been used over a finite planning period. The inflation rate changes from one periodic cycle to another following some probabilistic law. The optimal policy is determined so as to maximize the total profit over the planning horizon. Numerical examples are cited to illustrate the theoretical results, and a sensitivity analysis is carried out to examine the effect of the model parameters on the optimal policy.

An Inventory Model for Deteriorating Items with Price Dependent Demand and Delay in Payments under Stochastic Inflation Rate

The paper investigates the class of two-parameter log-logistic dose-response bioassay models in the binomial set-up. The dose is defined by the potency adjusted mixing proportions of two similar compounds. The aim is to investigate the Dand Dsoptimal mixture designs for estimating the full set of parameters or only the potency for a best guess of the parameter values. An indication has been given for finding the optimal design for the estimation of the mixture at which the probability of success attains a given value.

/pdf/optimum-mixture-designs-for-binomial-two-parameter-log-528q4odc6c.pdf

Optimum Mixture Designs for Binomial Two-Parameter Log-Logistic (LL2) Model with Mixture of Two Similar Compounds: Optimal design for log-logistic model (LL2)

SYNOPTIC ABSTRACTWe define skew-symmetric distributions based on the reflected generalized uniform distribution, a double compound gamma distribution and a double generalized Pareto distribution, all of which have symmetric density about zero. Expressions are derived for the probability density function (pdf), cumulative distribution function (cdf), and moments of the distributions. Several special functions are involved in the calculations.

Some Skew-Symmetric Reflected Distributions

In this paper, we investigate a mixture problem with two responses, which are functions of the mixing proportions, and are correlated with known dispersion matrix. We obtain D- and A-optimal designs for estimating the parameters of the response functions, when none or some of the regression coefficients of the two functions are the same. It is shown that when no prior knowledge about the regression coefficients is available, the D-optimal design is independent of the dispersion matrix, while the A-optimal design depends on it, provided the response functions are of different degree. On the other hand, when some of the regression coefficients are known to be the same for both the functions, the D-optimal design depends on the dispersion matrix when the two response functions are not of the same degree.

Manisha Pal

Papers

Optimal Regression Designs

An Inventory Model for Deteriorating Items with Price Dependent Demand and Delay in Payments under Stochastic Inflation Rate

Optimum Mixture Designs for Binomial Two-Parameter Log-Logistic (LL2) Model with Mixture of Two Similar Compounds: Optimal design for log-logistic model (LL2)

Some Skew-Symmetric Reflected Distributions

Optimum designs for parameter estimation in a mixture experiment with two correlated responses