Decentralised planning coordination with quantity discount contract in a divergent supply chain

This paper proposes to solve a supply chain planning problem with realistic features. The problem consists of planning productions, transportations and storage activities in a supply chain at a tactical level on a finite horizon. The main features considered are decentralised decision making and iteration of the planning process on a rolling horizon basis. In each planning process, the actors optimise their local planning and coordinate to achieve a good overall planning. A multi-agent system is used to model such supply chain behaviour. The study is conducted in a divergent two-echelon supply chain with one manufacturer and multiple independent retailers. Coordination is achieved using a standard contract in practice, known as the ‘quantity discount’ contract. The planning framework on the supply chain structure is detailed. Lot-sizing models integrating the quantity discount are presented for the local planning problems. Experimental tests are conducted with three major parameters: quantity discount price, quantity discount breakpoint and rolling horizon length. They are used to determine the quantity discount parameters in achieving the best supply chain profit, and to analyse the increasing profit of the actors. A decision-making tool which is able to consider realistic features of supply chain planning is therefore resulted.     

Multi-period channel coordination in vendor-managed inventory for deteriorating goods

This study examines the problem of optimally dynamic joint decisions, including replenishment scheduling/quantity, retail price, wholesale price, and revenue-sharing allocation, in a vertically decentralised single-manufacturer Stackelberg and single-retailer channel over a multi-period planning horizon, subject to deteriorating goods and multivariate demand function. This study uses a calculus-based formulation combined with dynamic programming techniques to solve the channel coordination decision problem. Additionally, three arrangements, namely price-only contract, revenue-sharing contract, and revenue-sharing plus linear rebate and side-payment contract for channel coordination, are developed under retailer-managed inventory (RMI) and vendor-managed inventory (VMI) systems, respectively. The analysis reveals that the proposed policy under the VMI system with the revenue-sharing plus linear rebate and side-payment contract tends to obtain low retail prices and large demand quantity, and results in near-perfect coordination, including greater system efficiency and Pareto improvements, for the vertically decentralised dynamic channel.     

A supply chain model with vendor-managed inventory,consignment, and quality inspection errors

This paper considers the integration between quality control and production inventory control in supply chain management. Specifically, we study the effect of inspection errors on the costs incurred in a supply chain system with a single vendor and multiple buyers. In this system, the vendor enters into a vendor-managed inventory (VMI) and a consignment stock (CS) partnership with several buyers. We assume that the items made by the vendor are not in perfect quality, but they contain a given proportion of defective units. We also assume that quality inspection of these items by the buyers is subject to sampling errors. Three cases indicating to different levels of supply integration are considered: VMI–CS system, traditional system and integrated system. For each case, a mathematical model is formulated, an optimum solution is developed, and a numerical example is solved.     

An optimised target-level inventory replenishment policy for vendor-managed inventory systems

In vendor-managed inventory (VMI) systems the supplier is responsible for replenishing customers and for deciding when and how much to deliver. One of two inventory policies is typically employed by the supplier. The first one, called the maximum level (ML) policy, gives full freedom to the supplier to deliver any quantity as long as it respects customer inventory capacities. The alternative, which is more constrained, is called the order-up-to (OU) policy. It states that the supplier has to bring the customer inventory up to its maximum capacity level upon delivery. We propose a new tactical policy in the context of VMI systems, called optimised target-level (OTL), under which when the supplier visits a customer, the quantity delivered is such that the final inventory will always be at the same customer-dependent OTL. We perform a computational evaluation of this new policy against both traditional strategies on benchmark instances. We show that it yields lower costs and inventory levels than the OU policy, and is only marginally more expensive than the ML policy, while being easier to implement.     

Impact of an emergency order opportunity on supply chain coordination

We consider a manufacturer-retailer supply chain in the pre-selling and selling seasons, whereby the manufacturer can offer the retailer an emergency order opportunity with a limited commitment quantity in addition to the regular order from the retailer before the selling season. Due to the short lead time for the emergency order, the manufacturer needs to prepare for it in the pre-selling season by producing more than the regular order or reserving its capacity for the responsive production. Through mathematically modelling and analyzing the supply chain, we found that, when the emergency order opportunity is provided, the manufacturer might be worse off, although the retailer is always better off. We derive the conditions whereby both the manufacturer and retailer can benefit from the emergency order, and the supply chain profit can be maximised. Further, we show that the supply chain can be coordinated by setting only the unit price and maximum commitment quantity for the emergency order. We also prove that Pareto improvement can be always achieved by setting the unit price for the regular order in addition to the unit price and maximum commitment quantity for the emergency order.     

Supply chain coordination with trade credit under the CVaR criterion

Trade credit is a popular payment method in the supply chain. However, it may transfer the market risk facing by the retailer to the manufacturer in the form of default risk. To reduce the default loss, we set up a modified newsvendor model incorporating random default probability. Under the goal of loss minimisation, the manufacturer’s optimal production quantity is derived with the criterion of conditional value at risk, and compared with the retailer’s optimal order quantity. It is found that, compared with traditional newsvendor setting, the setting of default possibility in trade credit can increase the order quantity but decrease the production quantity. If the risk aversion level and gross profit of product are low, the manufacturer may deliver below the quantity ordered. Although the default loss can be reduced by cutting order, the profits of both agents decrease, thereby leading to a deviation from the supply chain coordination. Trade credit coordinating the supply chain requires an extremely long credit period, which is not feasible. Moreover, quantity discount contract is able to improve the retailer’s order quantity, but insufficient to achieve coordination, which also depends on the manufacturer’s risk aversion level.     

Modelling on vendor-managed inventory policies with equal and unequal shipments under GHG emission-trading scheme

This paper studies five different stock control policies in the supply chain management. The lead time can be shortened by extra investment between two entities. The vendor produces a single product and delivers the order quantity in a number of unequal shipments to the buyer. The unit holding cost is divided into financial and storage components. The vendor takes care of financial component until the products are sold to the end customers to encourage them to buy more products. In order to reduce emissions from production and to protect the environment, some legislative actions have been taken such as implementing taxes and penalties. The cost function also includes these taxes and penalties. The optimal solutions of this constrained mixed integer non-linear programming problem are obtained by using the Genetic Algorithm (GA). Numerical examples are employed and comparison works are carried out with other existing literatures. Results show that the performance of the system is better when it is operated under unequal shipment policies and vendor-managed inventory (VMI) agreement.     

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.     

Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet

Traditional supply chain networks are often designed in the interests of a company. Once the network has been defined, the storage and distribution of goods are usually fixed and restricted within the network. This is assumed to be an inherent limit of current inventory control research. Instead of specialised hierarchical storage networks, this paper proposes an innovative vendor-managed inventory strategy exploiting the Physical Internet (PI), which is an open, universal, interconnected logistics system. In such a system, facilities and means of transport are shared and can be allocated according to demands of users. As a result, the PI allows users to stock anywhere in the network and also provides open multisourcing options for orders with on-demand warehousing services within the PI. Inventory decisions can be made dynamically by each player to minimise networkwide inventory levels. A non-linear, simulation-based optimisation model was developed for the vendors’ inventory decision-making when confronted with stochastic demands. A metaheuristic using simulated annealing was applied to solve the problem, and then, the optimised inventory decisions were validated using simulation. The results suggest that the proposed PI inventory model can reduce the total logistics cost while maintaining a comparable or better level of end customers’ services.     

Multi-period hedging and coordination in a prefabricated construction supply chain

In this paper, a multi-period buffer space hedging coordination between a building contractor (BC) and a logistics provider (LP) is investigated. In order to facilitate the application of the construction lead-time hedging (CLTH) strategy, adopted by the BC, extra buffer space needs to be reserved at LP’s intermediate warehouse for contingency usage. This strategy is defined as ‘buffer space hedging (BSH)’ and it increases the pressure of LP on involving extra storage and maintenance cost. Two coordination mechanisms are adopted for solving this BSH problem. One scheme is by introducing a cost-sharing term. A Nash game model is studied to find the individual optimal decisions. Another scheme is a cooperative game model with proper side-payments. We show that adjusting the BSH amount for each review period benefits the supply chain. Both coordination mechanisms enable a win–win outcome. Especially, if system resources are sufficient, the cooperative game outperforms the Nash game. Numerical experiments further demonstrate that the benefit of the proposed model is more significant under the case with lower unit enlarging/rearrangement cost, higher tardiness penalty and unpredictable and uncontrollable construction process-determined assembled and installed prefabs.     

A constrained EPSAC approach to inventory control for a benchmark supply chain system

The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.     

Quantity discount coordination for allocation of purchase orders in supply chains with multiple suppliers

Studies about supply chain coordination have emphasised maximising the profit of the overall supply chain, but the profit changes of individual members in the supply chain have often been overlooked. It has been shown that profit increment of the whole supply chain may not be beneficial for every individual member. Therefore, the use of quantity discounts to achieve the coordination of a supply chain is discussed in this article. A two-echelon selling system with a single buyer and multiple suppliers is considered to enhance profitability for both sides at the same time. An acceptable quantity discount condition for both the buyer and the suppliers to determine an appropriate order quantity allocation to produce more profits in the supply chain is proposed. Furthermore, the profit distribution between the buyer and each supplier is studied. Finally, the results of the numerical application show that the buyer should focus on managing the procurement costs to decrease the acquiring costs, and the suppliers should focus on the fixed costs of management to reduce the production costs in machine operations.     

Trust-embedded coordination in supply chain information sharing

This paper studies supply chain coordination with trust-embedded cost-sharing contract. In a two-tier supply chain, a retailer (she) and a supplier (he) make their private demand forecasting individually. The retailer places soft-orders, which are costless, non-verifiable and cancellable before shipping, to the supplier. After that, the supplier relies on the retailer’s ordering information to update his demand evaluation and prepare his capacity. How much the supplier relies on the retailer’s ordering information is specified by trust, which is a kind of psychological feeling and affected by multiple factors. When the supplier does not fully trust the retailer, he tends to prepare a conservative capacity to avoid over-production. To coordinate the supply chain, a two-stage coordination process is proposed. At the first stage, the supplier and retailer negotiate a cost-sharing rule to bind soft-orders. At the second stage, the retailer places a soft-order and decides whether or not to bind it referring to the cost-sharing rule. After that, the supplier determines his optimal production capacity. We show that the retailer and supplier value trust differently in the experimental studies. We also find that there is a threshold of negotiation power for the supply chain partners which means the supplier’s/retailer’s expected profit drops down if his/her negotiation power exceeds certain thresholds. The experimental studies also show that the proposed the two-stage coordination is effective.     

Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty

In this research, a problem of supply chain coordination with discounts under demand uncertainty is studied. To solve the problem, an Affinely Adjustable Robust Optimisation model is developed. At the time when decisions about order periods, ordering quantities and discounts to offer are made, only a forecasted value of demand is available to a decision-maker. The proposed model produces a discount schedule, which is robust against the demand uncertainty. The model is also able to utilise the information about the realised demand from the previous periods in order to make decisions for future stages in an adjustable way. We consider both box and budget uncertainty sets. Computational results show the necessity of accounting for uncertainty, as the total costs of the nominal solution increase significantly even when only a small percentage of uncertainty is in place. It is testified that the affinely adjustable model produces solutions, which perform significantly better than the nominal solutions, not only on average, but also in the worst case. The trade-off between reduction of the conservatism of the model and the uncertainty protection is investigated as well.     

Dual channel closed-loop supply chain coordination with a reward-driven remanufacturing policy

This paper investigates a reward-driven policy, employed in a closed-loop supply chain (CLSC), for acquiring used products earmarked for remanufacture. Under the examined model, a single manufacturer sells products through a retailer as well as directly to end users in a forward supply chain. In the reverse supply chain, three different modes of collection are employed to capture used products for remanufacture: they are through a third party, directly by the manufacturer and from the retailer. Mathematical models for both non-cooperative and centralised scenarios are developed to characterise the pricing decisions and remanufacturing strategies that indicate individual and overall supply chain performance. Optimality of all the proposed models is examined with theory. To coordinate and achieve a win–win outcome for channel members, we proposed a three-way discount mechanism for the manufacturer. Extended numerical investigation provides insights on ways to manage an efficient reward-driven CLSC in a dual-channel environment.     

Comparing different coordination scenarios in a three-level supply chain system

The consignment stock (CS) policy, independently or coupled with vendor managed inventory (VMI), has been practised by businesses and shown to be profitable. It helps to reduce or eliminate out-of-stock instances caused by fluctuations in demand. CS brings several benefits to collaborating parties. Unlike the two-level supply chain models in the literature, this paper considers a three-level supply chain that consists of a supplier, a vendor and a buyer with CS policy agreements. The paper also examines four coordination scenarios (a combination of traditional and CS) in conjunction with a payment scheme between adjacent parties. Nine coordination cases (models) are provided. A sensitivity analysis is performed to study the effects of some parameters on the performance of the developed models. Most of the results showed that a combination of traditional and CS policies returned a higher total system profit.     

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.     

Decision support system for vendor managed inventory supply chain: a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).     

Stockout propagation and amplification in supply chain inventory systems

We investigate the existence and magnitude of stockout propagation and stockout amplification in the context of supply chain inventory systems. Stockout amplification is a stage-to-stage increase in overall stockout rates. Stockout propagation is the tendency for stockout at one node to instigate a stockout at a neighbouring node and is conceptually related to the idea of cascading failures in physical systems, such as electrical power grids. We study these concepts in both upstream (‘supply side’) and downstream (‘demand side’) directions in the context of normal operating conditions for an adaptive R, S (periodic, order-up-to) inventory policy. We build a simulation model of a 5-stage serial supply chain that experiences normally distributed customer demands and gamma distributed lead times. We find that stockout propagation exists, but contrary to conventional wisdom, it occurs in the upstream direction. There is little indication that stockout propagation is occurring to any significant degree in the downstream direction. We also find stockout amplification occurring in the upstream direction in scenarios where more aggressively adaptive inventory parameter updating is performed. We discuss implications of this work in the areas of supply chain inventory modelling, ordering decisions, safety stock determination, and the use of adaptive inventory policies.     

Inventory performance of some supply chain inventory policies under impulse demands

This paper attempts to study the impact of impulsive demand disturbances on the inventory-based performance of some inventory control policies. The supply chain is modelled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). Under this setting, the behaviour of each inventory policy is analysed for inventory performance of each node. It is found that the independent decision-making by each node leads to a bullwhip effect in the supply chain whereby demand information is amplified and distorted. However, under a scenario where the retailer places a constant order irrespective of the end customer demand, the inventory variance was actually found to decrease along the supply chain. The variance of the inventory remained constant along the chain when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes. The results have significant industrial implications.