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

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

SIMULATING EXOGENOUS SHOCKS IN COMPLEX SUPPLY NETWORKS USING MODULAR STOCHASTIC PETRI NETS

Almost all major companies are embedded in complex, global supply networks, consisting of multiple nested supply chains, and building up a high level of complexity. Exogenous shocks on these networks (e.g. natural disasters) can directly and indirectly impact companies and even cause their entire supply network to fail. However, today it is extremely difficult for a company to predict the actual impact of an exogenous shock on its supply network. Hence, companies are not able to identify adequate counteractive measures. Therefore safeguarding measures are oftentimes insufficient or even counterproductive. This paper deals with modelling, analyzing and quantifying impacts of exogenous shocks on supply networks using Petri Nets. It provides means to simulate the vulnerability of different network constellations regarding exogenous influences. In order to evaluate the proposed method, we simulate different intensities of an exogenous shock delaying the delivery for an exemplary supply network. We thereby illustrate which results could be yielded from a real-world application. For our exemplary network we find that the marginal effect of a disruption declines with an increasing intensity of shock. Moreover, the impact of shocks can be mitigated by appropriate counteractive measures like in this example by an increased safety margin of stock

A Distributed Retail Beer Game for Decision Support System

AbstractA beer game is a simulation tool for the study of Supply Chain Management (SCM) issues used by the students of MIT. It has been augmented over the time to make it industry ready for decision making and risk management. Apart from smooth information and material flow among the distributed partners excess inventory is still an issue to control. In this paper, an attempt is made to improvise the Beer Game model to a Petri Net model for risk analysis and decision making. A successful simulation of the Petri Net model on efficient redistribution of stock towards inventory management is presented in this paper. The paper also establishes that the analysis is done in polynomial time

A value network development model and implications for innovation and production network management

In managing their value network, firms have to balance current and future value concerns and own and network partners’ concerns. Firms generate immediate value through manufacturing and selling the current generation of products together with other firms in its production network and generate future value by developing a new generation of products with other firms and research institutes in its innovation network. Product innovation and production often take place simultaneously and recurrently. We take the discernible production and innovation activities to occur in co-evolving network layers. We formulate a biplex value network development model that lays out the temporal pattern of production and innovation activities in the value network. We introduce terminology to pinpoint temporal interactions between the innovation and production activities. We study several exemplary complications in the cross-table of inter- and intragenerational interactions versus interactions within and across network layers