Critical Inventory Level Research Articles

A Supply Chain Inventory Management Method for Civil Aircraft Manufacturing Based on Multi-Agent Reinforcement Learning

Effective supply chain inventory management is crucial for large-scale manufacturing industries such as civil aircraft and automobile manufacturing to ensure efficient manufacturing. Generally, the main manufacturer makes the annual inventory management plan, and contacts with suppliers when some material is approaching critical inventory level according to the actual production schedule, which increases the difficulty of inventory management. In recent years, many researchers have focused on using reinforcement learning method to study inventory management problems. Current approaches were mainly designed for the supply chain with single-node multi-material or multi-node single-material mode, which are not suitable to the civil aircraft manufacturing supply chain with multi-node multi-material mode. To deal with this problem, we formulated the problem as a partially observable Markov decision process (POMDP) model and proposed a multi-agent reinforcement learning method for supply chain inventory management, in which the dual-policy and information transmission mechanism was designed to help the supply chain participant improve the global information utilization efficiency of the supply chain and the coordination efficiency with other participants. The experiment results show that our method has about 45% performance improvement on efficiency compared with current reinforcement learning-based methods.

Price and Lead time Disclosure Strategies in Inventory Systems

We consider a firm that faces the following pricing and leadtime disclosure decision. Either, (i) offer the same price to all arriving customers and disclose no leadtime information, in which case customers know only an expected leadtime, or, (ii) vary the price dynamically based on the current inventory status, and disclose leadtime information dynamically. The second option allows the firm to offer a price discount for a long leadtime, and to offer a short leadtime when it has a large inventory. In order to determine which pricing and leadtime disclosure policy attains higher maximum profit, we formulate and solve a Markov decision problem for each policy and compare the two solutions. The comparison suggests that, typically, there is a critical inventory level, above which static pricing and no leadtime disclosure yields higher profit, and, below that level, dynamic pricing and leadtime disclosure yields a higher profit. We also identify certain situations where the static policy leads to profits at least as large as those under the dynamic policy for any state, and we examine the price differences between the two policies. Finally, the structure of the solution is similar to the situation where the system manager can pause the production process, except that now this extra lever partly mitigates the superiority of the static policy.

Price and Leadtime Disclosure Strategies in Inventory Systems

We consider a firm that faces the following pricing and leadtime disclosure decision. Either, (1) offer the same price to all arriving customers and disclose no leadtime information, in which case customers know only an expected leadtime, or, (2) vary the price dynamically based on the current inventory status, and disclose leadtime information dynamically. The second option allows the firm to offer a price discount for a long leadtime, and to offer a short leadtime when it has a large inventory. In order to determine which pricing and leadtime disclosure policy attains higher maximum profit, we formulate and solve a Markov decision problem for each policy and compare the two solutions. The comparison suggests that, typically, there is a critical inventory level, above which static pricing and no leadtime disclosure yields higher profit, and, below that level, dynamic pricing and leadtime disclosure yields a higher profit. We also identify certain situations where the static policy leads to profits at least as large as those under the dynamic policy, for any state, and we examine the price differences between the two policies. Finally, the structure of the solution is similar to the situation where the system manager can pause the production process, except that now this extra lever partly mitigates the superiority of the static policy.

Impact of RFID technology on inventory control policy

RFID application can improve operation performance in a supply chain by reducing or eliminating inventory misplacement and shrinkage. In this paper, we present a periodic review inventory model to investigate and characterize the multiperiod inventory control policies in both non-RFID and RFID cases when the firm encounters misplacement and shrinkage. The optimal inventory control policy is proved to be a two-control limit policy. The control limits in both the non-RFID case and the RFID case are analyzed and examined, while considering the impact of shrinkage and misplacement on inventory policies. A critical inventory level is determined to identify the relationship of higher inventory level control limits between the RFID case and the non-RFID case. An intensive numerical study with sensitivity analysis of selling price, misplacement rate, shrinkage rate, inventory recovery rate, and tag price is conducted. We find that when RFID technology is adopted, the inventory control policy in the RFID case is much more stable than that of the non-RFID case, as the misplaced inventory can be recovered perfectly and instantly for sale and the inventory shrinkage can be reduced by RFID technology. In addition, one of our intriguing findings is that when the shrinkage rate is below a threshold value which is independent of parameters, RFID application has no effect on inventory control policy if the misplaced inventory can be recovered in a timely manner by physical audit, which has not been revealed in previous studies.

Inventory control policy of preventive lateral transshipment between retailers in multi periods

Purpose: Preventivelateral transshipment can respond to customers who will choose a substitute or to give up when the product is out of stock. Motivatedby the common practice, adecision-making model of preventive lateral transshipment with multi sellingperiods is developed. The purpose of the paper is to explore the optimal preventive lateral transshipment policy with multi selling periods. Design/methodology/approach: With adiscrete-time dynamic programming model, we take a dynamic programming approach and adopt backward induction to analyze two retailers’ preventive lateral transshipment policy. Findings: The optimal preventivelateral transshipment policy is a threshold policy which depends on both theremaining selling periods and inventory level. The above properties ensure thattwo retailers can control inventory with preventive lateral transshipment. Practical implications: The retailer can adjust inventory via the thresholdtype policy. The simple decisionrule which compares on-hand inventory level with the critical inventory level can be used to control inventory by preventive lateral transshipment. Originality/value: A discrete-timedecision-making model of preventive lateral transshipment policy isformulated. This model takes consideration of multi selling periods, whichis different from most existing researches on preventive lateraltransshipment.

INTEGRATED DECISION ON PRICING, PROMOTION AND INVENTORY MANAGEMENT

Firms often utilize promotion (such as coupons, advertisements, recruitment of excellent salespeople, and leafleting etc.) and dynamic adjustment of price to manage customers as well as proper production/inventory plan to satisfy the customers to get maximal profit in a firm. The decision on promotion and pricing and the decision on production/inventory must support each other. This paper addresses coordinated decision on pricing, promotion(non-price promotion) and inventory management. Specifically, we study a single item, periodic review model. The demand function is a linear demand function in which the market scale can be affected by the promotion conducted in that period. Unsatisfied demands are fully backlogged. We characterize the structure of the optimal policy that simultaneously determines the price, the promotion and the ordering quantity to maximize the total discounted profit with finite and infinite period problems. We show that the optimal replenishment policy is the quasi base stock list price target promotion policy, i.e., there exist a critical inventory level, a list price and a target promotion such that it is optimal to order up to the critical level, charge the list price and conduct the target promotion when the initial inventory is below the critical level and order nothing, conduct a higher promotion and charge a proper price to increase the demand otherwise. We also prove that the expected demand and the optimal promotion are increasing in the inventory, and price and promotion are complementary. Then we extend the problem to the case with capacity constraint. We show that the modified quasi base stock list price target promotion policy is optimal. For the joint decision problem on pricing, promotion and inventory control with positive fixed setup cost, we show that the optimal policy is (s, S, p, e) policy. That is, there exist two critical inventory levels stand St(st≤ St), a list price ptand a target promotion etin period t such that order up to St, charge price ptand conduct promotion etwhen the initial inventory is less than stand order nothing, charge a proper price and conduct a proper promotion otherwise.

Simulation-Based Approach for Calculating the Reliability of Logistic Support Process

Simulation-Based Approach for Calculating the Reliability of Logistic Support ProcessAny operational system, in order to successfully accomplish its intended mission, must rely on logistic support that will be available when required. Moreover, in many systems undesired event occurs later than components failure, if and only if repair is not completed within a grace period. Thus, in the paper there is considered the time dependent system of systems where the system total task must be executed during the constrained time resource. There is used the simulation approach to investigate the influence of parameters of the procurement process (order quantity, critical inventory level, lead-time length) and parameters of time resource on the system of systems behavior.

Inventory control in the presence of an electronic marketplace

This paper studies a periodic review inventory model in the presence of an electronic marketplace (EM). Emergency orders can be placed in the EM for additional cost, and excess inventory can be sold to the EM. When the order leadtime from the supplier is one period, the optimal inventory control policy is developed from a dynamic programming model of the problem. The policy is characterized by three critical inventory levels. When the order leadtime from the supplier is longer than one period, an EM policy is developed to determine the quantities of inventory to purchase from and sell to the EM in each period. Based on this EM policy, three ordering policies are proposed to determine the order quantity from the supplier. Numerical results show that significant cost reductions can be obtained by using the EM to adjust the inventory level in each period. The amount of cost reduction is greatly affected by system parameters, especially the order leadtime from the supplier and the costs for transactions in the EM.

Optimal replenishment for a periodic review inventory system with two supply modes

In this paper, we study periodic inventory systems with long review periods. We develop dynamic programming models for these systems in which regular orders as well as emergency orders can be placed periodically. We identify two cases depending on whether or not a fixed cost for placing an emergency order is present. We show that if the emergency supply mode can be used, there exists a critical inventory level such that if the inventory position at a review epoch falls below this critical level, an emergency order is placed. We also develop simple procedures for computing the optimal policy parameters. In all cases, the optimal order-up-to level is obtained by solving a myopic cost function. Thus, the proposed ordering policies are easy to implement.

A stochastic production/inventory system with all-or-nothing demand and service measures

This paper considers a one-product production/inventory system with intermittent production and random demands with the stipulation that the demand of a customer is completely lost when current inventory is not sufficient for the whole demand. Customers asking for the product arrive according to a Poisson process and the demands of the customers are independent and identically distributed random variables. The production facility is controlled by a two-critical-numbers rule under which production is stopped when inventory becomes sufficiently high and thd productionis restarted when inventory has dropped sufficiently low. Production occurs at a constant rate. In accordance with common practice we consider as service measures the fraction of demand that is lost and the fraction of customers that are lost. the problem is to find the critical inventory level below which production must be restarted in order to achieve a specific service level. For the special cases of exponential and deterministic demands an...