An enhanced approximation mathematical model inventorying items in a multi-echelon system under a continuous review policy with probabilistic demand and lead-time

An inventory system attempts to balance between overstock and understock to reduce the total cost and achieve customer demand in a timely manner. The inventory system is like a hidden entity in a supply chain, where a large complete network synchronizes a series of interrelated processes for a manufacturer, in order to transform raw materials into final products and distribute them to customers. The optimality of inventory and allocation policies in a supply chain for a cement industry is still unknown for many types of multi-echelon inventory systems. In multi-echelon networks, complexity exists when the inventory issues appear in multiple tiers and whose performances are significantly affected by the demand and lead-time. Hence, the objective of this research is to develop an enhanced approximation mathematical model in a multi-echelon inventory system under a continuous review policy subject to probabilistic demand and lead-time. The probability distribution function of demand during lead-time is established by developing a new Simulation Model of Demand During Lead-Time (SMDDL) using simulation procedures. The model is able to forecast future demand and demand during lead-time. The obtained demand during lead-time is used to develop a Serial Multi-echelon Inventory (SMEI) model by deriving the inventory cost function to compute performance measures of the cement inventory system. Based on the performance measures, a modified distribution multi-echelon inventory (DMEI) model with the First Come First Serve (FCFS) rule (DMEI-FCFS) is derived to determine the best expected waiting time and expected number of retailers in the system based on a mean arrival rate and a mean service rate. This research established five new distribution functions for the demand during lead-time. The distribution functions improve the performance measures, which contribute in reducing the expected waiting time in the system. Overall, the approximation model provides accurate time span to overcome shortage of cement inventory, which in turn fulfil customer satisfaction

Modeling the fraud-like investment founds by Petri nets

In this paper we model the fraud-like investment founds using place-transition Petri nets. We will also classify the business using regression line in order to find the possible fraud-like investment founds. In these regression lines we compute analytical the mark of a place in function of some other elements of the Petri net, and next we express this value in function of the same elements using regression. From the identity of the coefficients we find a ratio between two weights of arcs. We make also a program where the marks and transitions are implemented as classes for Petri nets, and, using the heritage mechanism we extend the Petri net to Petri net with priorities.Petri nets, fraud-like investment founds, objects programming.

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Simulación de una política de inventario basada en la metodología Demand Driven MRP desde un enfoque de redes de Petri

Context: Currently, companies are facing a problem associated with inventory control since there is a high number of references that they must manage to reduce lost sales and minimize low-turnover inventory. Method: Demand Driven MRP (DDMRP) is an innovative inventory control strategy that incorporates elements of Lean systems and theory of constraints which lead to the introduction of dynamic buffers with the purpose of controlling inventory levels while responding to the demand. Petri nets are used to simulate and validate the application of the DDMRP methodology in a finished product inventory. Results: From the conducted simulation, it is possible to verify the effectiveness of the DDMRP methodology for the case under study, where the overstock is reduced while the possibility of out-of-stock is minimized. Conclusions: The simulation of the DDMRP methodology through Petri nets allowed evaluating the performance of the policy before its implementation with the purpose of validating the effectiveness of the strategy on company performance indicators such as the level of service and costs storage.Contexto: En la actualidad, las compañías se enfrentan a una problemática asociada al control del inventario debido a que existe un alto número de referencias que se deben administrar con el objetivo de reducir las ventas perdidas y disminuir el inventario de baja rotación. Método: Demand Driven MRP (DDMRP) es una estrategia de control de inventarios innovadora que incorpora elementos de sistemas Lean y teoría de restricciones que llevan a introducir buffers dinámicos con el objetivo de controlar los niveles de inventario al tiempo que se responde a la demanda. Las redes de Petri se utilizan para simular y validar la aplicación de la metodología DDMRP en un inventario de producto terminado. Resultados: A partir de la simulación realizada, se logra comprobar la efectividad de la metodología DDMRP para el caso de estudio, en el que se reduce el sobrestock de inventario al mismo tiempo que se minimiza la posibilidad de agotados. Conclusiones: La simulación de la metodología DDMRP a través de redes de Petri permitió evaluar el funcionamiento de la política antes de su implementación, en aras de validar la efectividad de la estrategia sobre indicadores de desempeño de la compañía como el nivel de servicio y los costos de almacenamiento

Modeling the fraud-like investment founds by Petri nets

In this paper we model the fraud-like investment founds using place-transition Petri nets. We will also classify the business using regression line in order to find the possible fraud-like investment founds. In these regression lines we compute analytical the mark of a place in function of some other elements of the Petri net, and next we express this value in function of the same elements using regression. From the identity of the coefficients we find a ratio between two weights of arcs. We make also a program where the marks and transitions are implemented as classes for Petri nets, and, using the heritage mechanism we extend the Petri net to Petri net with priorities

Classification of the Existing Knowledge Base of OR/MS Research and Practice (1990-2019) using a Proposed Classification Scheme

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOperations Research/Management Science (OR/MS) has traditionally been defined as the discipline that applies advanced analytical methods to help make better and more informed decisions. The purpose of this paper is to present an analysis of the existing knowledge base of OR/MS research and practice using a proposed keywords-based approach. A conceptual structure is necessary in order to place in context the findings of our keyword analysis. Towards this we first present a classification scheme that relies on keywords that appeared in articles published in important OR/MS journals from 1990-2019 (over 82,000 articles). Our classification scheme applies a methodological approach towards keyword selection and its systematic classification, wherein approximately 1300 most frequently used keywords (in terms of cumulative percentage, these keywords and their derivations account for more than 45% of the approx. 290,000 keyword occurrences used by the authors to represent the content of their articles) were selected and organised in a classification scheme with seven top-level categories and multiple levels of sub-categories. The scheme identified the most commonly used keywords relating to OR/MS problems, modeling techniques and applications. Next, we use this proposed scheme to present an analysis of the last 30 years, in three distinct time periods, to show the changes in OR/MS literature. The contribution of the paper is thus twofold, (a) the development of a proposed discipline-based classification of keywords (like the ACM Computer Classification System and the AMS Mathematics Subject Classification), and (b) an analysis of OR/MS research and practice using the proposed classification

Modelling, optimisation and control of series supply chains and production processes

In recent years supply chains have gained the attention of both academia and industry. In this thesis, a novel state-space model of a multi-node supply chain is presented, controlled via local proportional inventory-replenishment policies. The model is driven by a stochastic sequence representing customer demand. The model is analysed under stationarity conditions, guaranteed to arise if the control parameters lie in a certain range which is identified and a simple recursive scheme is further developed for updating the covariance matrix of the system in closed form, i. e., as an explicit function of the control parameters. This allows us to analyse the effect of inventory policies on the "bullwhip effect" (demand amplification) for chains with an arbitrary number of nodes. The three-node model is subsequently analysed in detail under information sharing and the optimal policy is derived, which minimises inventory fluctuations (and inventory mean) under a probabilistic constraint related to downstream demand. It is shown that this policy can never lead to demand amplification in the chain, as long as the gain parameter of the downstream node lies in the stability region. Finally, issues related to estimation schemes based on local historical data are discussed. The main results and conclusions are illustrated via numerous examples and simulations. An alternative model of the supply chain is also developed using timed Hierarchical Coloured Petri Nets (HCPN). This approach considers supply chains as event-driven systems and studies decentralised control structures by analysing the impact of various continuous inventory policies and known forecasting methods followed by supply chain participants. CPN-Tools [fCPN] are used for the design of decision-making policies and simulation results are presented to highlight the main issues arising in real systems and to provide insights for future modelling and simulation work. Finally, a detailed case study is undertaken, for the production line of the "Bridngorth Aluminium Ltd" company which produces high quality rolled aluminium lithographic strips. An efficient representation for such production processes is provided and subsequently used for an extensive analysis and performance evaluation through appropriate metrics. In particular, the work addresses the implementation of an overall model in a simulation environment, capable of integrating the various aspects of the specific production management processes

Supply chain inventory control for the iron and steel industry

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