100% screening economic order quantity model under shortage and delay in payment

It is for a long time that the Economic Order Quantity(EOQ) model has been successfully applied to inventory management. This paper studies a multiproduct EOQ problem in which the defective items will be screened out by 0 screening process and will be sold after the screening period. Delay in payment is permissible though payment should be made during the grace period and the warehouse capacity is limited. Otherwise, there will be an additional penalty cost for late payment so the retailer would not be able tobuy products at discount prices.All-units and incremental discounts are considered for the products which dependon the order’s quantity just like the permissible delay in payment. Genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used to solve the proposed model and numerical examples are provided for better illustrations

A Study of Defense Logistics Agency Inventory Classifications: Application of Inventory Control Methods to Reduce Total Variable Cost and Stockage Levels

This thesis analyzes the financial impact of applying a single inventory requirements model to three separate classes of inventory at the Defense Logistics Agency\u27s (DLA) Defense Supply Center-Columbus (DSCC) commodity management facility. DLA\u27 5 blanket application of its variation of the Economic Order Quantity (EOQ) requirements model may not be appropriate for all levels of demand, possibly suboptimizing DLA\u27s desire to minimize inventory costs while still providing an appropriate level of customer service. Simulation analyses of the DLA EOQ requirements model, the Silver-Meal heuristic, and Periodic Order Quantity models were conducted to examine which dynamic lot-sizing model is more effective in minimizing inventory costs and levels for different levels of item demand. The Periodic Order Quantity model provided lower inventory levels and total variable costs than the DLA EOQ and the Silver-Meal models for the medium demand category. The DLA EOQ requirements model was found to provide lower inventory levels and total variable costs than either the POQ or the Silver-Meal models in the low and high demand categories

Static and dynamic inventory models under inflation, time value of money and permissible delay in payment

In this research a number of mathematical models were developed for static and dynamic deterministic single-item inventory systems. Economic factors such as inflation, time value of money and permissible delay in payment were considered in developing the models. Nonlinear optimization techniques were used to obtain the optimal policies for the systems.;First, a static single-item inventory model was considered in which shortages are allowed and a delay is permitted in payment. In this case, suppliers allow the customers to settle their accounts after a fixed delay period during which no interest is charged.;An extension of the model was then considered in which all cost components of the model are subject to inflation and discounting, with constant rates over the planning horizon. The mathematical model of the system was developed and a nonlinear optimization technique, Hooke and Jeeves search method, was used to obtain the optimal policies for the system.;A dynamic deterministic single-item inventory model was also considered in which the demand was assumed to be a linear function of time. Suppliers allow for a delay in payment and the cost components are subject to inflation and discounting with constant rates and continuous compounding. The Golden search technique was used to obtain the optimum length of replenishment cycle such that the total cost is minimized.;Computer applications using Visual Basic and Mathematics were developed and several numerical example were solved

An analysis of the effect of supply chain and manufacturing parameters on inventory cost reduction for push type manufacturing systems

In the global network of businesses, supply chain and order fulfillment managements are the most critical functional departments to determine the winner of the global competition. In this research a network of companies that are flowing information, product and services between providers and a receiver is investigated in order to gain a better insight of the current situation. Analyses, explanations and solutions were developed through responding to the following research questions: (1) What are the most important variables that affect the quality and delivery performances of a supply chain? (2) What are the most important variables that affect the service rate or fill rate of a supply chain of a manufacturing company? (3) What levels of the selected variables could be used in order to minimize inventory on hand? The research was based on the analysis of a supplier network of a midwestern manufacturing company. Initial study verified that there was no company policy established to prevent stock-outs resulting from late deliveries or quality nonconforming parts. In order to investigate the effects of existing company policies and guidelines a discrete event simulation model was developed. During the model building phase historic data was utilized to create simulation parameters. Analysis of the historic data revealed that neither the production lead time nor the schedule changes affect the quality or delivery performance of suppliers. The results of the simulation confirm the importance of the number of suppliers in a supply chain. The number of suppliers negatively affects the efficiency of the order fulfillment process and high numbers of suppliers require higher inventory levels. The company\u27s supplier classification guideline was also validated for delivery performance ratings by the simulation model. However, the supplier classification based on the quality performance was not found to be practically significant

Dynamic process modelling for business engineering and information systems evaluation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research is concerned with the pre-implementation evaluation of investments in Information Systems (IS). IS evaluation is important as organisations need to assess the financial justifiability of business change proposals that include (but usually are not limited to) the introduction of IS applications. More specifically, this research addresses the problem of benefits assessment within IS evaluation. We contend that benefits assessment should not be performed at the level of the IS application, as most extant evaluation methods advocate. Instead, to study the dynamics and the interactions of the IS applications with their surrounding environment, we propose to adopt the business process as the analytic lens of evaluation and to assess the impacts of IS on organisational, rather than on technical, performance indicators. Drawing on these propositions, this research investigates the potential of dynamic process modelling (via discrete-event simulation) as a facilitator of IS evaluation. We argue that, in order to be effective evaluation tools, business process models should be able to explicitly incorporate the effects of IS introduction on business performance, an issue that is found to be under-researched in previous literature. The above findings serve as the central theme for the development of a design theory of IS evaluation by simulation. The theory provides prescriptive elements that refer both to the design products of the evaluation and the design process by which these products can come into reality. The theory draws on a set of kernel theories from the business engineering domain and proposes a set of meta-requirements that should be satisfied by business process models, a meta-design structure that meets these requirements, and a design method that provides guidance in applying the theoretical propositions in practice. The design theory is developed and empirically tested by means of two real-life case studies. The first study is used to complement the findings of a literature review and to drive the development of the design theory's components, while the second study is employed to validate and further enhance the theory's propositions. The research results support the arguments for simulation-assisted IS evaluation and demonstrate the contribution of the design theory to the field

Dynamic Modeling and Analysis for Supply Chain

The objective of this study is to use system dynamics methodology to model the supply chain system and then present the optimal control to optimize the performance of supply chain by minimize the quadratic cost function while tracking and keeping the inventory close to target level. Under the system dynamics point of view, the supply chain was modeled as the continuous differential equation with lead time delay modeled as the first order delay model. In contrast to the frequency domain analysis of the classical control approach, the proposed control utilizes the time-domain state space representation with a set of input, output and state variables to build the dynamic system. On the other hand, by using the system dynamics it allows us to apply different control laws and analyze the dynamic behavior of system so that the decision policies can be found to improve the performance of supply chain. In this paper we employ the linear quadratic optimal control for such kind of supply chain dynamic system, the aim of controller is to find the control input as the order quantity to minimize the cost function and keep high customer satisfaction by tracking the target inventory level. Finally, the numerical simulation results are carried out in Matlab/Simulink environment and the performance of optimal controller will be compared with some classical control policies such as proportional and order-up-to level control policy. It is shown that our approach can obtain some good performances.Chapter 1. Introduction 1 1.1 Background 1 1.2 Motivation of this research 3 1.3 Research objectives 5 Chapter 2. Supply chain management and performance measurements 7 2.1 Supply chain management 7 2.2 Structure of supply chain management 10 2.3 Performance measurement of supply chain management 13 2.4 Process in supply chain management 15 Chapter 3. Dynamic modeling of supply chain 21 3.1 Production model 21 3.2 Transportation model 27 3.3 Distribution model 29 3.4 State-space of supply chain model 30 3.5 Costs function of supply chain 31 Chapter 4. Controller design 33 4.1 State-space model 33 4.2 Linear Quadratic Regular control design 33 4.3 Optimal tracking controller 35 Chapter 5. Simulation results 37 5.1 Demand and control parameters 37 5.2 Simulation results and analysis 38 Chapter 6. Conclusion 44 References 4

Inventory Model with Partial Backordering When Backordered Customers Delay Purchase after Stockout-Restoration

Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO) to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well

An EPQ Inventory Model with Allowable Shortages for Deteriorating Items under Trade Credit Policy

This paper attempts to obtain the replenishment policy of a manufacturer under EPQ inventory model with backorder. It is assumed here that the manufacturer delays paying for the received goods from the supplier and the items start deteriorating as soon as they are being produced. Based on these assumptions, the manufacturer’s inventory model is formulated, and cuckoo search algorithm is applied then to find the replenishment time, order quantity, and selling price with the objective of maximizing the manufacturer’s total net profit. Besides, the traditional inventory system is shown as a special case of the proposed model in this paper, and numerical examples are given to demonstrate better performance of trade credit. These examples are also used to compare the results of cuckoo search algorithm with genetic algorithm and investigate the effects of the model parameters on its variables and net profit

A Spreadsheet Model that Estimates the Impact of Reduced Distribution Time on Inventory Investment Savings: What is a Day Taken out of the Pipeline Worth in Inventory?

In most of the literature dealing with inventory problems, either with a deterministic or probabilistic model, lead time is viewed as a prescribed constant or a stochastic variable that is not subject to control. But in many practical situations, lead time can be reduced by an extra crashing cost; in other words, it is controllable. This study proposes a repeatable spreadsheet optimization model that estimates the impact of reduced replenishment lead time on inventory investment savings at forward and strategic locations to motivate decision makers to support enterprise-wide distribution process improvement. The study provides users with a means of automatically calculating inventory control parameters such as safety stocks and reorder points, and automatically estimating the savings caused by lead time mean or variability reduction. A trade-off analysis can be done to determine whether reducing lead time would override the lead time crashing cost. First, the model finds the optimal safety factor of an item based on a fill rate goal using Excel Solver. Then, Excel\u27s VBA automates the process of finding safety factors for other items before and after lead time reduction. Finally, the model is applied to three different supply support activities to illustrate its superior features, which include allowing the user to change and upgrade it for future research

Three-Echelon Inventory Model with Permissible Delay in Payments under Controllable Lead Time and Backorder Consideration

This paper proposes a three-echelon inventory model with permissible delay in payments under controllable lead time and backorder consideration to find out the suitable inventory policy to enhance profit of the supply chain. In today’s highly competitive market, the supply chain management has become a critical issue in both practice and academic and supply chain members have to cooperate with each other to bring more benefits. In addition, the inventory policy is a key factor to influence the performance of the supply chain. Therefore, in this paper, we develop a three-echelon inventory model with permissible delay in payments under controllable lead time and backorder consideration. Furthermore, the purpose of this paper is to maximize the joint expect total profit on inventory model and attempt to discuss the inventory policy under different conditions. Finally, with a numerical example provided here to illustrate the solution procedure, we may discover that decision-makers can control lead time and payment time to enhance the performance of the supply chain