It is developed and presented an approach to inventory management EOQ-model optimization in this paper taking into the deferrals provided for the order cost payments. They summarize the results for the traditional EOQ-models taking into account the deferrals of payments which relate to payment of the batch of goods, with the payment of storage costs, and of the delivery costs payment. Presented modifications of EOQ-formulas will allow for managers to while considering the above features also to take into account he specificity costs of storage charging, in the form of rent, and for the used place on stock, to improve the decisions on the organization of the supply chain quality.
The article presents a special modification of the EOQ-formula for a diversified EOQ-model of inventory management with account to specifics of lot deliveries. It will allow managers to determine the optimal parameters of the inventory management strategy if it is required to take into account the following features: 1) the possibility of order payment deferral; 2) time value of money at cashflow modelling 3) incomes specifics, when the proceeds come with a delay 4) specificity of storage costs payment (in form of rent or by the occupied storage space). In addition, the article specifies some options related to the possibility of using such a formula if it is necessary to additionally take into account: a) the restriction on the allowable length of the delay in payment of goods, so that the point of receipt of the proceeds did not exceed the corresponding reorder interval duration (on average); b) the vehicle capacity. The presented research materials on optimization of supplies will allow managers to estimate the effect of permissible delays in order payments, delays in receipt of proceeds, and the factor of vehicle capacity on the parameters of the optimal strategy of inventory management. The procedures of EOQ formula modification for inventory management systems are performed in relation to interesting and business-relevant models of this type that correspond to efficient deliveries, where these delays allow to make order payments from revenue at reordering intervals.
The article presents the derived formulas for calculating the parameters of the EOQ model that takes into account simultaneous multi-product supplies and differential discounts as well as the developed algorithm for calculating the parameters of this model.
This book concentrates on in-depth explanation of a few methods to address core issues, rather than presentation of a multitude of methods that are popular among the scientists. An added value of this edition is that I am trying to address two features of the brave new world that materialized after the first edition was written in 2010. These features are the emergence of “Data science” and changes in student cognitive skills in the process of global digitalization. The birth of Data science gives me more opportunities in delineating the field of data analysis. An overwhelming majority of both theoreticians and practition-ers are inclined to consider the notions of ‘data analysis” (DA) and “machine learning” (ML) as synonymous. There are, however, at least two differences between the two. First comes the difference in perspectives. ML is to equip computers with methods and rules to see through regularities of the environment - and behave accordingly. DA is to enhance conceptual understanding. These goals are not inconsistent indeed, which explains a huge overlap between DA and ML. However, there are situations in which these perspectives are not consistent. Regarding the current students’ cognitive habits, I came to the conclusion that they prefer to immediately get into the “thick of it”. Therefore, I streamlined the presentation of multidimensional methods. These methods are now organized in four Chapters, one of which presents correlation learning (Chapter 3). Three other Chapters present summarization methods both quantitative (Chapter 2) and categorical (Chapters 4 and 5). Chapter 4 relates to finding and characterizing partitions by using K-means clustering and its extensions. Chapter 5 relates to hierarchical and separative cluster structures. Using encoder-decoder data recovery approach brings forth a number of mathematically proven interrelations between methods that are used for addressing such practical issues as the analysis of mixed scale data, data standardization, the number of clusters, cluster interpretation, etc. An obvious bias towards summarization against correlation can be explained, first, by the fact that most texts in the field are biased in the opposite direction, and, second, by my personal preferences. Categorical summarization, that is, clustering is considered not just a method of DA but rather a model of classification as a concept in knowledge engineering. Also, in this edition, I somewhat relaxed the “presentation/formulation/computation” narrative struc-ture, which was omnipresent in the first edition, to be able do things in one go. Chapter 1 presents the author’s view on the DA mainstream, or core, as well as on a few Data science issues in general. Specifically, I bring forward novel material on the role of DA, including its successes and pitfalls (Section 1.4), and classification as a special form of knowledge (Section 1.5). Overall, my goal is to show the reader that Data science is not a well-formed part of knowledge yet but rather a piece of science-in-the-making.
The sections of the discipline "Economic and mathematical methods and models in logistics" are presented, related to procedures for optimizing supply chains on the basis of methods of mathematical theory of inventory management, methods and models of graph theory, methods for solving the transport problem, methods for optimizing flows in networks, optimizing network project schedules. The foundations of the method of simulation are given.
The article presents a model of optimization of inventory control strategy in terms of risk in the supply chain enterprises meat industry. On study the approach to the transformation of the model under conditions of uncertainty in the model of risk management by using the method of decision tree. Based on the method of decision tree for the corresponding model in terms of risk determine the optimal strategy, which provides a different attitude to risk.
This paper presents a preliminary analysis of hotel room prices in several European cities based on the data from Booking.com website. The main question raised in the study is whether early booking is advantageous indeed, and if so, how early should it be? First a script was developed to download more than 600 thousand hotel offers for reservations from 25 March 2013 to 17 March 2014. Then an attempt to discover more details concerning the early booking effect was made via basic statistics, graphical data representation and hedonic pricing analysis. It was revealed that making reservations in advance can be really gainful, although more data and research are needed to measure the exact numbers, as they depend on at least seasonality and city.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.