Bullwhip effect and inventory oscillations analysis using the beer game model

This work examines the bullwhip effect generated and suffered by each level of a four-stage beer game supply chain when different demand scenarios are considered. The paper shows that the actors who generate lower bullwhip are those who suffer more from its effects. Moreover, a new definition of an inventory oscillations measure based on bullwhip definition is introduced. Finally the paper verifies that the new measure of inventory oscillations provides more information on supply chain performance than the bullwhip measure.     

Joint pricing and inventory strategies in a supply chain subject to inventory inaccuracy

This paper focuses on pricing strategies, inventory policies for a supply chain when Radio Frequency Identification (RFID) technology is adopted to cope with inventory inaccuracy. The supply chain consists of one supplier and one retailer, in which the RFID tag price is shared between the supplier and the retailer. We present and compare the performance differences between a wholesale price contract and a consignment contract when the retailer is the Stackelberg leader and the supplier is the follower. Based on the optimal pricing and inventory decisions, an interesting observation of contract selection is that there are two critical values of inventory available rate such that when the inventory availability is less than the lower value, both the supplier and the retailer prefer a consignment contract; when the inventory availability is greater than the upper value, a wholesale price contract is their best choice; when the inventory availability is between the two values, the supplier prefers a wholesale price contract and the retailer prefers a consignment contract. Additionally, there exist threshold values of RFID tag price and sharing rate to determine the contract preference for the retailer. Furthermore, the profits of both the supplier and the retailer are independent of the RFID tag price sharing rate in a wholesale price contract, and the supplier has the incentive to invest in RFID tag cost in a consignment contract.     

Applying genetic algorithms to dampen the impact of price fluctuations in a supply chain

Genetic Algorithms (GAs) have been identified as an innovative and useful approach for dampening the Bullwhip Effect along supply chains. This paper extends previous work by developing an improved supply chain model that incorporates additional cost factors such as ordering cost, item cost, distribution cost and production cost. The revised model is then used to examine one element of the Bullwhip Effect, i.e. price fluctuation strategies. A GA is employed to determine the ordering policy for each member in the model that minimises cost. The research illustrates how the GA performs if a sales promotion is introduced. From the experimental results, it is shown that a GA can help determine an improved ordering policy and reduce the total cost across the supply chain.     

Decentralized inventory control in a two-stage capacitated supply chain

This paper investigates a two-stage supply chain consisting of a capacitated supplier and a retailer that faces a stationary random demand. Both the supplier and the retailer employ base stock policies for inventory replenishment. All unsatisfied demand is backlogged and the customer backorder cost is shared between the supplier and the retailer. We investigate the determination of decentralized inventory decisions when the two parties optimize their individual inventory-related costs in a noncooperative manner. We explicitly characterize the Nash equilibrium inventory strategies and identify the causes of inefficiency in the decentralized operation. We then study a set of simple linear contracts to see whether these inefficiencies can be overcome. Finally, we investigate Stackelberg games where one of the parties is assumed to be dominating.     

Lateral inventory transshipment problem in online-to-offline supply chain

Online-to-offline (OTO) is a new commercial model with enormous market potential. Online customer orders are forwarded to the offline brick-and-mortar store to fulfil, which is a combination of dual-channel supply chain. OTO overcomes many disadvantages of the traditional dual-channel supply chain, but still faces uncertain market demand. To reduce the inventory risk caused by demand uncertainty, lateral inventory transshipment is employed in this paper to pool inventory risk in OTO supply chain. We model centralised OTO and decentralised OTO with/without transshipment, and then analyse different scenarios. Our results demonstrate that there exists a unique Nash equilibrium of inventory order levels in dual channels and an optimal transshipment price to maximise the profit of the entire supply chain. Finally, we provide a numerical example of uniform demand distribution. Our analyses offer many managerial insights and show that transshipment always benefits the OTO supply chain.     

Risk pooling via unidirectional inventory transshipments in a decentralized supply chain

We study risk pooling via unidirectional lateral transshipments between two locations under local decision-making. Unidirectional transshipments can be applicable when cost structures and/or capabilities differ between locations, and it is also a common practice in dual channel supply chains with online and offline sales channels. We show that such a system cannot be coordinated only with varying transshipment prices. The transshipment receiver orders more and the transshipment giver orders less than the respective optimal centralised order quantities. In order to remove this discrepancy, we suggest horizontal coordination mechanisms by introducing a leftover subsidy for the location providing the transshipments or a shortage subsidy for the location receiving transshipments as well as a combination of shortage and leftover subsidy. Further, we evaluate the impact of network structure by comparing the equilibrium order quantities and profits under the uni- and bidirectional systems as well as a system without transshipments. Since demand correlation is a critical aspect in risk pooling we provide a detailed numerical study to discuss its impact on our findings.     

Effective investment to reduce lost-sales rate in a periodic review inventory model

In 1973 Montgomery et al. proposed an (R, T) type of a periodic review inventory model in which the lost-sales rate caused by stockout is given. The purpose of this article is to investigate in this heuristic periodic review inventory model with partial lost-sales to effectively increase investment and to reduce the lost-sales rate. We discuss two models: complete (normal distribution) and partial (distribution free) information about the protection interval (i.e., review period plus lead time) demand distribution. For each model, two commonly used investment cost functional forms, logarithmic and power, are employed for lost-sales rate reduction. That is, for these two investment cost functions, we first assume that the protection interval demand follows a normal distribution, and then we assume that only first and second moments of the probability distribution of protected interval demand are known. Two algorithms are developed to find the optimal investment decision, and six numerical examples are given to illustrate the results.     

Bullwhip effect and complexity analysis in a multi-channel supply chain considering price game with discount sensitivity

This paper constructs a multi-channel supply chain that includes a manufacturer, a dual-channel retailer and an online retailer. The dual-channel retailer has a traditional channel and an online channel, while the manufacturer cooperates with the retailers and opens a direct channel simultaneously. The horizontal and historical price discount sensitivities are taken into account to establish the price-sensitive demand functions. A price game model with the heterogeneous expectations is proposed and analysed with the methods of the stability domain, the bifurcation diagram and the maximum Lyapunov exponent. The complexity and bullwhip effect of each channel are investigated with respect to the price adjustment speed and historical price discount sensitivity. The results show that a moderate or low price discount sensitivity keeps the system stable and a high price discount sensitivity brings the system into the twofold cycle state or chaotic state. It is interesting that if both online channels increase the adjustment speeds with similar strategy the system will enter chaos through the Neimark–Sacker bifurcation. The bullwhip effect is affected by the price adjustment speed and the price discount sensitivity, especially in the double-period or chaotic state, where the bullwhip of the overall supply chain is increased significantly. The results show that controlling price discount sensitivity is useful for supply chain node companies.     

Modelling a complex supply chain: understanding the effect of simplified assumptions

The benefits of coordinating activities and consolidating distribution points in supply chains are well highlighted and intuitively logical. However, the impact of these decisions on the overall performance of a complex supply chain may not be as obvious as usually perceived. This study models a relatively complex supply chain and evaluates the impact of simplifying demand and lead time assumptions under various supply chain configurations. Of particular interest is the investigation of the effect of risk pooling and the synchronization of production cycles in a multi-level multi-retailer supply chain under the influence of various parameters such as batch size, delivery frequency and ordering cycle. This study highlights the extent of complicated interaction effects among various factors exist in a complex supply chain and shows that that the intricacy of these effects can be better understood with a simulation model.     

Integration of closed loop distribution supply chain network and 3PRLP selection for the case of battery recycling

The increased use of lead acid batteries in automotive vehicles will increase the demand for lead and to meet this increasing demand used batteries are identified as a most important source of lead through recycling. Since recycled lead is a costly commodity, the market potential for reclaiming the secondary lead from the used batteries has been growing. For this purpose, a multi-echelon, multi-product closed loop distribution supply chain (CLDSC) network is designed and integrated with the selection process of best third-party reverse logistics provider (3PRLP) to achieve cost efficiency and delivery schedules in reverse logistics. A fuzzy multi-criteria decision-making (FMCDM) model based on the VIKOR method is used for the selection of best 3PRLP. To optimise the proposed network, a mixed integer linear programming model is developed and solved using LINGO 8.0 optimisation software package for the case of battery recycling and decisions are made regarding raw material procurement from the supplier, production, distribution and amount of reclaimed/recycled material. Since the main aim of this study is to optimise the CLDSC network, the supply chain cost of the forward distribution supply chain network is found and compared with the total supply chain cost of the CLDSC network and the results show that a cost reduction can be achieved in the case of CLDSC network. Finally, model experiments for varying rate of returns are conducted to study the percentage of cost savings.     

Pre-positioning inventory and service outsourcing of relief material supply chain

Service outsourcing is very common in a commercial supply chain, and in humanitarian relief area, the transportation service is usually outsourced. To practice relief supply more effectively, it seems essential to enlarge outsourcing from shipping to more areas, and private enterprises could play a vital role. This paper examines the optimal pre-disaster order quantity of a certain relief commodity, based on a two-stage coordinated approach. Our findings show that the delay cost, shortage penalty cost, risk of supply shortage, salvage value, expected perishable rate, unit inventory cost and reactive price have significant impacts on the optimal amount of propositioned inventory. Moreover, the outsourcing strategies differ by types of relief commodities. For perishable supplies, proactive or reactive outsourcing would improve the benefits of buyer and supplier simultaneously. As for imperishable supplies, it is better to combine proactive insourcing approach and reactive outsourcing strategy. In view of some supplies whose monitoring cost is high, the insourcing approach is much better than the outsourcing approach.     

基于供应链的企业库存成因及优化控制研究（二）

基于企业全面库存的管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出了库存控制的相应对策,以实现全面库存优化,提高经营效益.     

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.     

基于供应链的企业库存成因及优化控制的研究（一）

基于企业全面库存的管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出了库存控制的相应对策,以实现全面的库存优化,提高经营效益。     

Quantity discount versus lead time-dependent discount in an inter-organizational supply chain

Supply chain management refers to the integrated management of a set of activities from the ordering and receiving of raw material through manufacturing of products to the distribution and delivery to the customers. One of the main mechanisms used to coordinate the efforts of an inter-organizational supply chain are incentive systems. This research uses simulation to compare two incentive systems: quantity versus lead time-dependent discounts. The empirical results showed that discount systems do make a difference in the gross profit for the individual members of the supply chain. The paper also provides managerial implications for possible implementation of this research.     

Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments

Firms currently operate in highly competitive scenarios, where the environmental conditions evolve over time. Many factors intervene simultaneously and their hard-to-interpret interactions throughout the supply chain greatly complicate decision-making. The complexity clearly manifests itself in the field of inventory management, in which determining the optimal replenishment rule often becomes an intractable problem. This paper applies machine learning to help managers understand these complex scenarios and better manage the inventory flow. Building on a dynamic framework, we employ an inductive learning algorithm for setting the most appropriate replenishment policy over time by reacting to the environmental changes. This approach proves to be effective in a three-echelon supply chain where the scenario is defined by seven variables (cost structure, demand variability, three lead times, and two partners’ inventory policy). Considering four alternatives, the algorithm determines the best replenishment rule around 88% of the time. This leads to a noticeable reduction of operating costs against static alternatives. Interestingly, we observe that the nodes are much more sensitive to inventory decisions in the lower echelons than in the upper echelons of the supply chain.     

Algorithm for constructing a delivery-sequencing/inventory-allocation plan for supply chain control in the operational planning level

This paper aims to propose an algorithm to construct a delivery-sequencing/inventory-allocation plan used to control a supply chain in the operational planning level. The algorithm which is mainly based on the improving search technique begins by determining a suitable initial sequence of customer orders, allocating available inventory and determining inventory replenishment plan according to the sequence, calculating the interesting goals, and finally searching the appropriate sequence of customer orders using a proposed pairwise interchange technique. The sequence of the customer order is considered appropriate if it can simultaneously give most preferable two goals: minimizing the total penalties paid by the supply chain, and minimizing the average cost of fulfilling each product unit transferred to customers. The efficiency of the proposed algorithm is tested by the numerical experiments based on real data from a selected supply chain in Thailand, namely the food-ingredient industry. Statistical results show that the proposed algorithm significantly outperforms the current planning heuristics used in the industry and some other well-known heuristics.     

A periodic-review inventory model in a fluctuating environment

We study a single-item periodic-review inventory model in a fluctuating environment with a fixed lead time of λ periods. The state of the environment at the beginning of each period is described by a homogeneous Markov chain. Ordering, holding, penalty costs and the distributions of random variables representing the customer's demand and the supplier's capacity level are state environment dependent. By using dynamic programming it is proved in the finite-horizon case that the optimal policy is of a base stock type. Its parameters are monotonic in the number of the periods making up the horizon and also in stochastically ordered random variables representing different supplier capacities. Similar results are proved for the infinite-horizon problem.     

Dual-channel closed loop supply chains: forward channel competition,power structures and coordination

This paper examines the effect of forward channel competition and power structure on dual-channel closed loop supply chains (CLSC), which consists of a manufacturer, a retailer and a collector. The manufacturer can either wholesale products to the retailer or directly sell them to the market, the collector undertakes the collection activity of used products. Under different channel power structures, a centralised and three decentralised models are explored under symmetric and asymmetric relative status between direct and retail channels. Through a comprehensive comparison among these models, the result shows that each channel member has an incentive to play the channel leader’s role. Meanwhile, from the total channel system’s perspective, we find that the manufacturer-led or retailer-led model can either be the most effective CLSC under symmetric relative channel status, which depends on the channel substitution rate between two channels. While under asymmetric relative channel status, the numerical result shows that the whole CLSC should select collector-led, manufacturer-led and retailer-led CLSC model in turn with the retail channel’s relative status becoming stronger. Finally, with the benchmark of the centralised decision-making system, we design modified two-part tariff contracts to coordinate dual-channel CLSCs under different channel power structures.     

Vendor managed inventory with consignment stock for supply chain with stock- and price-dependent demand

This paper presents a single vendor–single buyer coordinated model. The vendor produces a single deteriorating item and transfers it to the buyer in equal shipments. The model is based on vendor managed inventory with consignment stock (VMI-CS) agreement in which the vendor uses the buyer’s warehouse. The buyer stocks items both on his shelf and in his warehouse. The demand is assumed to be linearly sensitive to inventory level and selling price. The objective is to determine variables that maximise the total profit. An exact solution procedure is proposed to find the optimal solution. Numerical results show that supply chain members will benefit from the advantages of economies of scale in coordinated model with VMI-CS policy.