1,720,958 research outputs found
Optimal inventory policies with postponed demand by price discounts
No full textThis thesis introduces a demand postponement policy in order to improve the performance of inventory management under batch ordering, advance demand information, capacitated/ uncapacitated and periodic/continuous review inventory systems. The main aim of this study is to find integrated demand postponement and inventory policies. The structure of the thesis consists of five main chapters which starts with an introduction in Chapter 1 which summarizes the main objectives of the study with a background information, followed by a Chapter 2 presenting an overview of the relevant literature and the methodology. Chapter 3 as the first research paper, an inventory problem with stochastic demand and batch ordering and lost sales based on a real case is introduced and a demand postponement policy applied on this system to convert some of the lost sales to advance demand. A Markov Decision Process model is proposed and it is solved through Linear Programming (LP). The dual of the primal model is used to reduce the computational effort and it is tested with several numerical data sets. The optimal inventory policy and discount policy for different batches are shown for managerial insights. In Chapter 4, the same problem without batch ordering is formulated by Markov Decision Process (MDP) solved by Backward induction algorithm. In addition, the demand pattern is changed to Advance Demand Information (ADI) which combines both stochastic and deterministic demand. The properties of optimal inventory and postponement policy parameters are analyzed and the numerical experiments are carried out under the uncapacitated and capacitated systems to show the impact of the postponement policy. The comparison of policy parameters with the literature shows that the demand postponement policy is highly effective for the efficient use of capacity. In Chapter 5, the extension of the problem to a continuous review inventory system with distribution strategies is studied by an Net Present Value (NPV) approach. The effectiveness of demand postponement under different financial settings are examined and an extensive numerical experiments are presented. The thesis ends with a conclusion in Chapter 6 including the summary of the results, limitations of the study and further research directions
Improving inventory system performance by selective purchasing of buyers’ willingness to wait
No full textWe develop a demand postponement mechanism to improve the performance of a single item, periodic review inventory system with advance demand. The focus in the literature has been on how to stimulate customers towards advance demand. Predicting how demand will shift can be problematic, however, and backorders may still occur. We focus on how a firm can address backorders under a given advance de- mand pattern by a mechanism of compensation from which both the firm and the customers will benefit: the firm may offer a discount to customers for accepting later deliveries at a promised delivery date. De- livery postponement offers are made selectively, i.e. in some periods and to some customers only when there is a benefit for the firm to do so. Customers may decline the offer, but then face the probability of a backorder. In each period, the firm has to decide whether to make delivery postponement offers and for how long, and whether to order from its supplier and how much. We formulate the problem as a Markov Decision Process and solve it by backward induction. Numerical examples illustrate the properties of the state-dependent policies obtained for both uncapacitated and capacitated inventory systems. The postponement mechanism in capacitated systems leads to policies that differ from the threshold policy identified as optimal in the literature. Overall, the approach shows promise to improve system performance more efficiently compared to strategies aiming to increase advance demand in the system
Increasing the performance of a hospital department with budget allocation model and machine learning assisted by simulation
No full textThe COVID-19 pandemic highlighted the critical need for efficient resource management in healthcare. In this study, the internal medicine outpatient clinic in a hospital is modelled by simulation method. Appropriate statistical distributions of the parameters are derived from past data. The results of a limited number of simulation runs are used as training data for machine learning techniques and an estimation model is selected among them. The estimation results are considered as input to a mathematical model which determines the optimal budget allocation for improving the system performance. Analysis considers patient waiting times and system throughput under varied parameters. A significant amount of time is saved by using machine learning to predict the simulation model outcomes, which had previously taken a total of around 7 hours reduced to 30-40 minutes. Time savings through machine learning are projected to be notably greater for more complex simulations comparing to current case
Batch ordering inventory management under the mixed demand information: a case study
No full textThis study is concerned with analysing the past demand data and development of an inventory model with demand arising from deterministic which is known in advance and random sources simultaneously. Two different shortages are created for each demand type and in order to prevent model to backlog the deterministic demand, very high shortage cost is given for deterministic demand. The numerical value of the parameters are obtained from a real case which the inventory system of an information and technological organization of a university. The main difference of this study from the previous studies is that the order amount must be in palette quantity for a deterministic and stochasticdemand inventory problem. Under this constraint, an inventory model is developed and tested with several datasets. Assuming lead time as constant, the value of deterministic demand present in the system and impact of palette constraint are investigated. These investigations are compared with the status quo in the case study. It has seen that the palette quantity behaves as safety stock for high level random demand. Recommendations based on the impacts of advance demand information, lead time and pallet quantity are presented in terms of changing in ordering costs, holding costs and service level
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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