Mathematical Modelling Solutions for Stock and Cost Dependent Inventory in a Limited Display Space Warehouse

Study in this paper is concerned with optimization of both quantity of order and selling price together, considering EOQ model for items with depreciating nature. It is based on the few assumptions like rate of demand is dependent on level of stock displayed on shelf as well as per unit selling rate, also, the space for stock display is finite. Two mathematical models are studied to investigate the further revised EOQ modelling for obtaining maximum profits and also develop models for such optimized solutions. Justification and analysis of the work developed and studied is done through sensitivity analysis and numerical examples

Supply Chain Coordination under Trade Credit and Quantity Discount with Sales Effort Effects

The purpose of this paper is to investigate the role of trade credit and quantity discount in supply chain coordination when the sales effort effect on market demand is considered. In this paper, we consider a two-echelon supply chain consisting of a single retailer ordering a single product from a single manufacturer. Market demand is stochastic and is influenced by retailer sales effort. We formulate an analytical model based on a single trade credit and find that the single trade credit cannot achieve the perfect coordination of the supply chain. Then, we develop a hybrid quantitative analytical model for supply chain coordination by coherently integrating incentives of trade credit and quantity discount with sales effort effects. The results demonstrate that, providing that the discount rate satisfies certain conditions, the proposed hybrid model combining trade credit and quantity discount will be able to effectively coordinate the supply chain by motivating retailers to exert their sales effort and increase product order quantity. Furthermore, the hybrid quantitative analytical model can provide great flexibility in coordinating the supply chain to achieve an optimal situation through the adjustment of relevant parameters to resolve conflict of interests from different supply chain members. Numerical examples are provided to demonstrate the effectiveness of the hybrid model

An integrated inventory model with capacity constraint and order-size dependent trade credit

[[abstract]]Trade credit has many forms in today’s business practice. The most common form of trade credit policy that is used to encourage retailers to buy larger quantities is order-size dependent. When the number of ordered units exceeds the capacity of the own warehouse, an additional rented warehouse is required to store the excess units. Therefore, to incorporate the concept of order-size dependent trade credit and limited storage capacity, we proposed an integrated inventory model with capacity constraint and a permissible delay payment period that is order-size dependent. In addition, the unit production cost, which is a function of the production rate, is considered. Three theorems and an algorithm are developed to determine the optimal production and replenishment policies for both the supplier and the retailer. Finally, numerical examples are presented to illustrate the solution procedure and the sensitivity analyses of some key parameters are provided to demonstrate the proposed model.[[notice]]補正完畢[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]電子

Inventory Management and Supply Chain Coordination Mechanisms

This dissertation is on inventory management and supply chain coordination mechanisms within an economic order quantity framework. Specifically, this research focuses on modeling optimal order policies and coordination mechanisms for a supply chain involving items which experience probabilistic failure during storage. These items are common types of manufactured items which, nonetheless, require specialized order policy considerations due to their unique characteristics. We first develop the solution for the buyer’s problem through the use of an economic order quantity (EOQ) model incorporating item failure. We then proceed to model the manufacturer’s problem through the use of an economic production quantity (EPQ) model. Finally, we consider mechanisms to promote mutually-beneficial cooperation between the supplier and n buyers in service of coordinating the entire supply chain. While prior research has focused on items which can be repaired or sold at a discount upon failure, such models are inappropriate for systems where repair costs exceed or are equivalent to item costs and imperfect items are unacceptable. Examples of industries featuring these inventory conditions include the medical, defense, and electronics industries where defective items are largely useless. First, our EOQ model considers a buyer-supplier relationship featuring delivery and stocking of items which experience probabilistic failure in storage. Thereafter, our EPQ model considers in-house production of such items. Collectively, our EOQ and EPQ models provide methods for developing optimal order policies necessary to achieve practicable supply chain coordination. In order to validate the necessity of the developed models, we include an empirical analysis of item reliability for some common mechanical components used in the defense industry, thereby identifying items which fail in the manner modeled in this dissertation. Having considered optimal order policies for both buyers and suppliers, we next develop an optimal solution for a coordinated supply chain. The proposed solution allows the manufacturer to coordinate a supply chain consisting of n buyers in order to achieve a common replenishment time. Through this optimization framework, we minimize total system-wide costs and derive the cost savings associated with our coordinated solution. Numerical examples are then used to demonstrate the magnitude of cost savings achievable through our coordination framework. We conclude by proposing several mechanisms for leveraging the resulting cost savings to induce mutually-beneficial cooperation between the supplier and multiple buyers. Given the lack of buyer-supplier cooperation noted in empirical research related to supply chain coordination, our identification of specific mechanisms useful for inducing mutually-beneficial cooperation between buyers and suppliers represents an important practical contribution to the supply chain coordination literature. These models are accompanied by a thorough overview and discussion of economic order quantity theory, optimal order policies, and supply chain coordination mechanisms.Ph.D., Business Administration -- Drexel University, 201

Machine learning approach for credit score analysis : a case study of predicting mortgage loan defaults

Dissertation submitted in partial fulfilment of the requirements for the degree of Statistics and Information Management specialized in Risk Analysis and ManagementTo effectively manage credit score analysis, financial institutions instigated techniques and models that are mainly designed for the purpose of improving the process assessing creditworthiness during the credit evaluation process. The foremost objective is to discriminate their clients – borrowers – to fall either in the non-defaulter group, that is more likely to pay their financial obligations, or the defaulter one which has a higher probability of failing to pay their debts. In this paper, we devote to use machine learning models in the prediction of mortgage defaults. This study employs various single classification machine learning methodologies including Logistic Regression, Classification and Regression Trees, Random Forest, K-Nearest Neighbors, and Support Vector Machine. To further improve the predictive power, a meta-algorithm ensemble approach – stacking – will be introduced to combine the outputs – probabilities – of the afore mentioned methods. The sample for this study is solely based on the publicly provided dataset by Freddie Mac. By modelling this approach, we achieve an improvement in the model predictability performance. We then compare the performance of each model, and the meta-learner, by plotting the ROC Curve and computing the AUC rate. This study is an extension of various preceding studies that used different techniques to further enhance the model predictivity. Finally, our results are compared with work from different authors.Para gerir com eficácia a análise de risco de crédito, as instituições financeiras desenvolveram técnicas e modelos que foram projetados principalmente para melhorar o processo de avaliação da qualidade de crédito durante o processo de avaliação de crédito. O objetivo final é classifica os seus clientes - tomadores de empréstimos - entre aqueles que tem maior probabilidade de pagar suas obrigações financeiras, e os potenciais incumpridores que têm maior probabilidade de entrar em default. Neste artigo, nos dedicamos a usar modelos de aprendizado de máquina na previsão de defaults de hipoteca. Este estudo emprega várias metodologias de aprendizado de máquina de classificação única, incluindo Regressão Logística, Classification and Regression Trees, Random Forest, K-Nearest Neighbors, and Support Vector Machine. Para melhorar ainda mais o poder preditivo, a abordagem do conjunto de meta-algoritmos - stacking - será introduzida para combinar as saídas - probabilidades - dos métodos acima mencionados. A amostra deste estudo é baseada exclusivamente no conjunto de dados fornecido publicamente pela Freddie Mac. Ao modelar essa abordagem, alcançamos uma melhoria no desempenho do modelo de previsibilidade. Em seguida, comparamos o desempenho de cada modelo e o meta-aprendiz, plotando a Curva ROC e calculando a taxa de AUC. Este estudo é uma extensão de vários estudos anteriores que usaram diferentes técnicas para melhorar ainda mais o modelo preditivo. Finalmente, nossos resultados são comparados com trabalhos de diferentes autores

Sulautettu ohjelmistototeutus reaaliaikaiseen paikannusjärjestelmään

Asset tracking often necessitates wireless, radio-frequency identification (RFID). In practice, situations often arise where plain inventory operations are not sufficient, and methods to estimate movement trajectory are needed for making reliable observations, classification and report generation. In this thesis, an embedded software application for an industrial, resource-constrained off-the-shelf RFID reader device in the UHF frequency range is designed and implemented. The software is used to configure the reader and its air-interface operations, accumulate read reports and generate events to be reported over network connections. Integrating location estimation methods to the application facilitates the possibility to make deploying middleware RFID solutions more streamlined and robust while reducing network bandwidth requirements. The result of this thesis is a functional embedded software application running on top of an embedded Linux distribution on an ARM processor. The reader software is used commercially in industrial and logistics applications. Non-linear state estimation features are applied, and their performance is evaluated in empirical experiments.Tavaroiden seuranta edellyttää usein langatonta radiotaajuustunnistustekniikkaa (RFID). Käytännön sovelluksissa tulee monesti tilanteita joissa pelkkä inventointi ei riitä, vaan tarvitaan menetelmiä liikeradan estimointiin luotettavien havaintojen ja luokittelun tekemiseksi sekä raporttien generoimiseksi. Tässä työssä on suunniteltu ja toteutettu sulautettu ohjelmistosovellus teolliseen, resursseiltaan rajoitettuun ja kaupallisesti saatavaan UHF-taajuusalueen RFID-lukijalaitteeseen. Ohjelmistoa käytetään lukijalaitteen ja sen ilmarajapinnan toimintojen konfigurointiin, lukutapahtumien keräämiseen ja raporttien lähettämiseen verkkoyhteyksiä pitkin. Paikkatiedon estimointimenetelmien integroiminen ohjelmistoon mahdollistaa välitason RFID-sovellusten toteuttamisen aiempaa suoraviivaisemin ja luotettavammin, vähentäen samalla vaatimuksia tietoverkon kaistanleveydelle. Työn tuloksena on toimiva sulautettu ohjelmistosovellus, jota ajetaan sulautetussa Linux-käyttöjärjestelmässä ARM-arkkitehtuurilla. Lukijaohjelmistoa käytetään kaupallisesti teollisuuden ja logistiikan sovelluskohteissa. Epälineaarisia estimointiominaisuuksia hyödynnetään, ja niiden toimivuutta arvioidaan empiirisin kokein

An evaluation of marketing research techniques in three case studies

Thesis (M.B.A.)--Boston Universit