Optimizing order policy and credit term for items with inventory-level-dependent demand under trade credit limit

Under the combined effects of inventory-level-dependent demand(ILDD)and trade credit,the retailer is able to order more quantities to stimulate market demand.However,from the supplier's perspective,two important issues are lacking sufficient attention.First,during the credit period,the retailer's higher order quantities imply increases in both the retailer's account payable and the supplier's opportunity cost of capital.Second,given the supplier's fixed production rate,the increased market demand may drive the capacity utilization to be variable.Thus,by formulating a supplier-dominated system,this paper incorporates trade credit limit(TCL)to address its effects on optimal policies vis-a-vis the item with ILDD.Specifically,three indicators can be proposed to reveal which type of financing policy the retailer should choose.Moreover,based on TCL,the supplier can effectively manage the retailer's order quantity and the corresponding account payable.Additionally,the retailer's maximum allowable order quantity is developed to ensure that the supplier can supply the retailer's order quantity on time.Furthermore,when the effects of ILDD become more significant,the manufacturer will reduce the maximum allowable order quantity to control the retailer's order incentive.

Effect of Ordering Policies on Complex Dynamics Behaviours in a Discrete-Type Manufacturing Industry Supply Chain System

The beer game model is a typical paradigm used to study complex dynamics behaviours in production–distribution systems. The model, however, does not accord with current practical supply chain system models in discrete?type manufacturing industry, which are generally composed of retailers, distributors, manufacturers with internal sup?ply chain, and suppliers. To describe how ordering policies influence the complex dynamics behaviour modes and operating cost in a general discrete?type manufacturing industry supply chain system, a high dimension piecewise?linear dynamics model is built for the supply chain system. Five kinds of ordering policy combination are considered. The distribution of both the largest Lyapunov exponent of e ective inventory and average operating cost per cycle is obtained by simulation in a policy space. The simulation shows that for the general discrete?type manufacturing industry supply chain system, the upper chaotic corners emerge besides the lower chaotic corners in the policy space expressing the distribution of system behaviour mode, and that the ordering policies at each supply chain node as well as their combination have very significant e ect on the topology of the distribution of both system behaviour mode and operating cost in the policy space. We find that chaos is not always corresponding to high cost, and the "chaos amplification" is not completely relevant to the "cost amplification".

OPTIMUM ORDERING POLICY FOR PREVENTIVE AGE REPLACEMENT

Most of the spare ordering policies treated up to now have assumed that preventive and corrective replacement costs are equal, which implies in essential that there is no significant need for preventive replacement. This paper presents an ordering policy for preventive age replacement with minimal repair. Introducing the replacement, repair, inventory holding and shortage costs, the expected cost rate is derived. A procedure to determine jointly the ordering time for a spare and the preventive replacement time for the operating unit so as to minimize the expected cost rate is proposed. To explain the ordering policy and the optimization procedure, a numerical example is also included.

Optimal ordering policy for platelets:Data-driven method vs model-driven method

Platelets,one of the most significant materials in treating leukemia,have a limited shelf life of approximately five days.Because platelets cannot be manufactured and can only be centrifuged from whole or donated blood directly,an accurate ordering policy is necessary for the efficient use of this limited blood resource.Given this motivation,the present study examines an ordering policy for platelets to minimize the expected shortage and overage.Rather than using the two-step model-driven method that first fits a demand distribution and then optimizes the order quantity,we solve the issue using an integrated datadriven method.Specifically,the data-driven method works directly with demand data and does not rely on the assumption of demand distribution.Consequently,we derive theoretical insights into the optimal solutions.Through a comparative analysis,we find that the data-driven method has a mean anchoring effect,and the amounts of shortage and overage reduced by this method are greater than those reduced by the model-driven method.Finally,we present an extended model with the service level requirement and conclude that the order decided by the data-driven method can precisely satisfy the service level requirement;however,the order decided by the model-driven method may be either higher or lower than the service level requirement and can lead to a higher cost.

Information Sharing in a Multi-Echelon Inventory System

The influence of different information sharing scenarios in a single supplier-single retailer supply chain is analyzed. The five information sharing scenarios are centralized information sharing, full information sharing, supplier-dominated information sharing, retailer-dominated information sharing, and noninformation sharing. Iterative procedures are developed to obtain the inventory policies and the system costs at equilibrium points. Numerical examples show that the cost of a centralized inventory system is about 20% - 40% lower than that of a decentralized system with non-information sharing. Furthermore, a higher information sharing level does not always lead to a lower system cost in a decentralized supply chain due to inventory competition.

Monitoring and Limiting Deceptive Counterfeiting:a Two-Stage Model

Over past decades,deceptive counterfeits which cannot be recognized by ordinary consumers when purchasing,such as counterfeit cosmetics,have posed serious threats on consumers’health and safety,and resulted in huge economic loss and inestimable brand damages to the genuine goods at the same time.Thus,how to effectively control and eliminate deceptive counterfeits in the market has become a critical problem to the local government.One of the principal challenges in combating the cheating action for the government is how to enhance the enforcement of relative quality inspection agencies like industrial administration office(IAO).In this paper,we formulate a two-stage counterfeit product model with a fixed checking rate from IAO and a penalty for holding counterfeits.Tominimize the total expected cost over two stages,the retailer adopts optimal ordering policies which are correlated with the checking rate and penalty.Under certain circumstances,we find that the optimal expected cost function for the retailer is first-order continuous and convex.The optimal ordering policy in stage two depends closely on the inventory level after the first sales period.When the checking rate in stage one falls into a certain range,the optimal ordering policy for the retailer at each stage is to order both kinds of products.Knowing the retailer’s optimal ordering policy at each stage,IAO can modify the checking rate accordingly to keep the ratio of deceptive counterfeits on the market under a certain level.