基于线性时变需求的鲜活农产品三级供应链协调

针对一个供应商-分销商-零售商构成的鲜活农产品三级供应链,基于线性时变需求,利用时间折扣契约实现了供应链的协调,并求出了使供应链各节点企业达到共赢的契约参数的取值范围。同时对产品变质率的变化率θ和需求量的变化率b进行了敏感性分析,提出在时间折扣契约的基础上,零售商通过加强库存管理也可以有效延长供应链的最优订货周期。     

DISCOUNTING DECISIONS IN A SUPPLIER-BUYER RELATIONSHIP WITH A LINEAR BUYER'S DEMAND

In this paper, we analyze discounting decisions for a supplier with a group of homogeneous customers. We focus on two aspects: the gaming nature of the discount problem and the demand consideration in the process. We use a general quantity discount schedule and start with the Stackelberg equilibrium of the problem. It is shown that, for the seller to gain from quantity discount, he has to set up his quantity discount schedule such that the buyer will order more than his EOQ. Both the seller and the buyer can gain significantly from quantity discount. The incentive for discount is twofold: reducing inventory related cost and attracting more demand from the customers. In addition, quantity discount schedule can be very efficient in obtaining the maximum gain the seller and the buyer can possibly obtain together.     

An integrated inventory optimization model for facility location-allocation problem

This paper presents an integrated inventory distribution optimisation model for multiple products in a multi-echelon supply chain environment. Inventory, transportation and location decisions are considered. The objective is to offer practical guideline to the steel retail supply chain practitioners in choosing the correct distribution centre, finding out inventory level at individual inventory keeping points (retailers and distribution centres) point thereby helping them in reducing overall distribution cost. The framework presented endorses systems approach and suggests near-optimal approach to calculating inventory for an individual distributor and his retailers. Two algorithms are used to solve this problem, a novel hybrid Multi-objective Self-learning particle swarm optimiser and Non-dominated sorting genetic algorithm-II. The model and solution methods are tested on real data-sets obtained from organisations in the steel retail environment. The actual data on inventory holding, ordering and transportation costs of distributors and retailers are used as inputs. The decisions like choosing correct set of Distribution centres, keeping optimal regular and safety stock inventory levels are arrived at by applying practical constraints in the supply chain. Model developed assists in effective and efficient distribution of the products manufactured from the optimal location at minimal cost.     

Inventory policies analysis under demand patterns and lead times constraints in a real supply chain

This paper reports a study on a real three-echelon supply chain operating in the beverage sector. The authors, starting from the actual supply chain configuration, propose a detailed study of the inventory systems. The test of a comprehensive set of different operative scenarios, in terms of customers’ demand intensity, customers’ demand variability and lead times, becomes a powerful tool for inventory systems analysis along the supply chain. The main objective is the comparison of the actual supply chain configuration with optimistic and pessimistic scenarios for studying the behaviour of different inventory control policies and optimizing the inventory system of each supply chain node. Due to the dynamically changing and stochastic behaviour of the supply chain variables as well as the complex interactions among its actors, the authors have been pushed to implement an advanced simulation model supported by a ‘well-planned’ experimental design. In addition the paper aims to underline the research effort for conceptualizing, modelling, validating and simulating a real stochastic supply chain.     

基于横向补货的库存协调近似模型

以给定零售商独自拟定订货策略为前提,提出了一种在横向补货允许的情况下,能够有效地刻画系统库存的近似模型.该模型在"最近邻居"优先补货原则下,详细地阐述了系统中的产品需求走势和相应的需求满足率.并通过和仿真试验的数值结果进行比较,验证了该模型的有效性,还对横向补货允许和补货不允许两种不同情况下的系统库存成本进行了比较,形象地给出了横向补货策略在优化库存成本方面的绩效.关于单个零售商订货策略一般性的拓展以及系统联合订货策略的可能性研究也给予了相关说明.     

A comprehensive analysis of the Newsvendor model with unreliable supply

A single-period, uncertain demand inventory model is analyzed under the assumption that the quantity ordered (produced) is a random variable. We first conduct a comprehensive analysis of the well known single period production/inventory model with random yield. Then, we extend some of the results existing in literature: our main contribution is to show that earlier results are only valid for a certain range of system parameters. Under the hypothesis that demand and the error in the quantity received from supplier are uniformly distributed, closed-form analytical solutions are obtained for all values of parameters. An analysis under normally distributed demand and error is also provided. The paper ends with an analysis of the benefit achieved by eliminating errors.     

Texting while driving as impulsive choice: A behavioral economic analysis

The goal of the present study was to examine the utility of a behavioral economic analysis to investigate the role of delay discounting in texting while driving. A sample of 147 college students completed a survey to assess how frequently they send and read text messages while driving. Based on this information, students were assigned to one of two groups: 19 students who frequently text while driving and 19 matched-control students who infrequently text while driving but were similar in gender, age, years of education, and years driving. The groups were compared on the extent to which they discounted, or devalued, delayed hypothetical monetary rewards using a delay-discounting task. In this task, students made repeated choices between $1000 available after a delay (ranging from 1 week to 10 years) and an equal or lesser amount of money available immediately. The results show that the students who frequently text while driving discounted delayed rewards at a greater rate than the matched control students. The study supports the conclusions that texting while driving is fundamentally an impulsive choice made by drivers, and that a behavioral economic approach may be a useful research tool for investigating the decision-making processes underlying risky behaviors.     

Models for integrated production-inventory systems: steady state and cost analysis

We consider a two-echelon production-inventory system with a central supplier connected to production systems (servers) at several locations, each with a local inventory. Demand of customers arrives at each production system according to a Poisson process and is lost if the local inventory is depleted. To satisfy a customer’s demand, a server at the production system takes exactly one unit of raw material from the associated local inventory. The central supplier manufactures raw material to replenish the local inventories, which are controlled by a continuous review base stock policy. We derive stationary distributions of joint queue length and inventory processes in explicit product form. After performing a cost analysis, we find out that the global search for the vector of optimal base stock levels can be reduced to a set of independent optimisation problems. The explicit form of the stationary distribution enables us to get additional structural insights, e.g. about monotonicity properties and stability conditions. Obtaining the product form relies on some simplifying assumptions. The results are therefore compared with simulations of a more realistic system, which supports to use it as approximation.     

Switchgear component commonality design based on trade-off analysis among inventory level,delivery lead-time and product performance

The shortening of product delivery lead-times can usually be achieved by keeping high-level components in inventory, however in small-volume production systems, maintaining such inventories is often a costly as well as a risky business strategy. If the risk of maintaining unsold inventory can be decreased, even small-volume manufacturers may be able to justify holding more significant quantities of versatile inventory. This paper discusses a component commonality effect to breakthrough the trade-off relationship between inventory levels and delivery lead-times for such small-volume production systems. By using the same component in different products, inventory maintenance costs can be dramatically reduced, but component commonality design problems are inherently complex, since excessive module commonality may lead to lower product performances, and there are trade-off relationships between product performance and cost reductions obtained through component commonality. In this paper, such a design problem is formulated as a multiobjective component commonality design optimisation problem considering inventory level, delivery lead-time and product performance, and the optimal solutions are obtained as a Pareto optimal solution set. Detailed procedures concerning the proposed design method, including inventory simulation, are discussed and developed for a switchgear design problem. Finally, an example switchgear design problem is solved to illustrate that optimal use of component commonalities across different modules can significantly reduce inventory costs, while also shortening product delivery lead-times.     

Performance analysis for automated storage and retrieval systems

Automated storage and retrieval (AS/R) systems have had a dramatic impact on material handling and inventory control in warehouses and production systems. A unit-load AS/R system is generic and other AS/R systems represent its variations. Common techniques that are used to predict performance of a unit-load AS/RS are a static analysis or computer simulation. A static analysis requires guessing a ratio of single cycles to dual cycles, which can lead to poor prediction. Computer simulation can be time-consuming and expensive. In order to resolve these weaknesses of both techniques, we present a stochastic analysis of a unit-load AS/RS by using a single-server queueing model with unique features. To our knowledge, this is the first study of a stochastic analysis of unit-load AS/R systems by an analytical method. Experimental results show that the proposed method is robust against violation of the underlying assumptions and is effective for both short-term and long-term planning of AS/R systems.     

Evaluation of divergent N-echelon (s,nQ)-policies under compound renewal demand

In this paper, decentralized inventory control in a divergent multi-echelon network is considered. All stockpoints are controlled by continuous review (s,nQ)-installation stock policies. Due to the fact that orders from a stockpoint to its predecessors may have to wait, this delay must be incorporated into the lead time of an arbitrary replenishment. We develop analytical approximations for the first two moments of this waiting time. These results enable us to accurately approximate the relevant performance characteristics at each stockpoint, given its (s,nQ)-policy. The performance measure considered in this paper are fill rate and average physical inventory. The analysis can easily be extended for other performance measures. The main contribution of this paper is the fact that the results apply to arbitrary divergent multi-echelon systems, with stochastic transportation times, arbitrary lot sizes and compound renewal demand. Correspondence to: Gudrun P. Kiesmüller     

Lead-time analysis and a control policy for production lines

We address a control problem for a production line that produces one product to stock and faces random demand. During stockouts, the system quotes a fixed response time for each arriving order, and the customers place their orders only if the response time promised meets their deadlines. Customer orders are filled on a first come, first served basis. A penalty cost is incurred whenever a customer is served later than promised. A two-parameter admission/inventory control policy is implemented that maintains a bounded backlog and a constant inventory position (total inventory minus backlog) in the system. For production lines with exponential processing times and Poisson demand, the mean profit rate of the system is computed analytically using closed queueing network formulae. For systems with general processing or interarrival time distributions, the profit rate is estimated via simulation. Simple properties are established that ensure that the profit maximising control parameters can be determined in finite time using exhaustive search. Numerical results show that the proposed policy performs better than the make-to-order/zero-inventory and the lost-sales/make-to-stock policies.     

Optimal inventory policies for uniform replenishment systems with time-dependent demand

This study develops an analysis of lot size inventory systems where the replenishment rate is uniform and demand follows a power demand pattern. Shortages are not allowed. Holding cost, replenishing cost and purchasing cost are considered in inventory system control. The objective of the study is to find the economic production quantity that minimises total inventory cost per unit of time. We conclude that optimal inventory policies depend on the demand pattern index chosen to represent customer demand. Theoretical results are illustrated with a business case study. A sensitivity analysis is proposed to describe the optimal policy behaviour.     

Evaluating long-term service performance under short-term forecast updates

Managing product availability in a cost-effective way has always been a major challenge faced by inventory managers. We study the problem of a firm selling a perishable product with short-term demand patterns and a long-term service target using the newsvendor framework. The newsvendor determines his long-term order at the first stage, and revises the order according to a short-term forecast update at the second stage. He also evaluates a long-term service target for his overall performance on product availability across all possible forecast updates. We characterise his optimal inventory policy that minimises the expected inventory cost while meeting the long-term service target. Both in-stock rate and fill rate targets are examined.     

Dynamic pricing for multiple class deterministic demand fulfillment

We consider how a firm should allocate inventory to multiple customer classes that differ based on the price they pay and their willingness to incur delay in fulfillment of their demand. The problem is set in a deterministic demand, economic-order-quantity-like environment with holding, backorder, lost demand and setup costs. The firm either fulfills demand or offers a price discount to induce the demand to wait for fulfillment from the next reorder. We determine the optimal policy and discuss how changes in various parameters affect profitability, customer service, and operational measures such as order frequency and base stock levels. We compare the results to a policy that only rations inventory without dynamic discounting and to a policy that only provides discounts. Through the comparison, we observe that dynamic pricing can be seen as a combination of a pricing mechanism which determines demand and an allocation mechanism that differentiates between customer classes, serving each ones needs. We show that if lower-value customers are distinguished by accepting reduced service, it is possible that both high and low-value customer classes see better levels of service under the optimal policy than under a discounting only policy. In addition we demonstrate the applicability of the results to a stochastic version of the problem.     

DETERMINISTIC APPROXIMATIONS FOR INVENTORY MANAGEMENT AT SERVICE FACILITIES

We consider the problem of finding optimal inventory policies for a service facility where the demand for inventory occurs during the provision of service (e.g., fixing a car in a repair shop). The paper formulates a model where both the demand and service rates are assumed to be constant and deterministic. Consequently a queue forms only during stockouts. In the first of two models analyzed, the service rate is assumed to be fixed and cannot be controlled by the service facility. The ability to use this simple, deterministic model to approximate systems with probabilistic arrival and/or service distributions is also analyzed. The second model relaxes the assumption of a fixed service rate. Optimal inventory policies are derived under linear costs over ordering, inventory holding, customer waiting, and the service rate.     

Optimising installation (R,Q) policies in distribution networks with stochastic lead times: a comparative analysis of guaranteed- and stochastic service models

This paper studies two modelling approaches to the multi-echelon inventory optimisation problem in a distribution network with stochastic demands and lead times. It compares the performance of a novel guaranteed-service model (GSM), using an installation (R, Q) inventory control policy, with a stochastic service model (SSM) considering ordering, holding and flexibility costs. From both cycle service level and fill rate perspectives, our numerical analysis of the 1-warehouse 2-retailer network shows that cost difference between both models is driven by the internal service level at the warehouse. The GSM outperforms the SSM for over 80% of the simulated instances and realises an average total cost improvement of approximately 10%. This analysis goes against earlier results that showed a relatively low-cost difference between the two approaches, and demonstrates that it is worthwhile to evaluate competing models for multi-echelon inventory optimisation in real-world supply chains with batch ordering and variable lead times.     

A note on evaluating the risk in continuous review inventory systems

This paper is an attempt to evaluate the long term risk of stock-out and obsolescence in continuous review inventory systems, typically of slow-moving but very critical items. Inventory decisions depend very much on the goodness of the estimates of the input parameters like the holding, ordering and stock-out costs. It is a well-known fact that stock-out cost is a very difficult parameter to estimate. The lower it is the lower the quality of service will be while the higher it is the higher the inventory cost would be and possibly higher obsolescence rate too. In this paper, we develop a framework to evaluate the risks, in the long term, of stock-out and obsolescence, especially for inventory of critical spares whose demand rate is not high. For this purpose, we propose the use of quasi-stationary distributions for continuous review (r, Q) inventory systems with the condition that the Laplace transforms of functions of interest are rational algebraic functions. We relate the quasi-stationary distribution to the conditional tail expectation which is a coherent risk measure used in finance and actuarial studies. Numerical illustration is also provided.     

可回复多级库存系统的最优订货和回复策略

本文建立的可回复装配多级库存系统由两部分组成：缺陷零部件库存和产成品库存,其中产成品库存既可以通过零件维修、装配来补充,也可以直接从外部采购产成品获得。模型假设产品由两个可回复零件组成,且回收速率和外部需求是稳定的。通过建模和分析,得到了最优外部采购的经济订货批量,以及最佳装配策略和零件存储策略。     

Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand

A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.