On the optimal lot-sizing and scheduling problem in serial-type supply chain system using a time-varying lot-sizing policy

In this paper, we solve the optimal sequencing, lot-sizing and scheduling decisions for several products manufactured through several firms in a serial-type supply chain so as to minimise the sum of setup and inventory holding costs while meeting given demand from customers. We propose a three-phase heuristic to solve this NP-hard problem using a time-varying lot- sizing approach. First, based on the theoretical results, we obtain candidate sets of the production frequencies and cycle time using a junction-point heuristic. Next, we determine the production sequences for each firm using a bin-packing method. Finally, we obtain the production times of the products for each firm in the supply chain system by iteratively solving a set of linear simultaneous equations which were derived from the constraints. Then, we choose the best solution among the candidate solutions. Based on the numerical experiments, we show that the proposed three-phase heuristic efficiently obtains feasible solutions with excellent quality which is much better than the upper-bound solutions from the common cycle approach.     

Return policy and supply chain coordination with network-externality effect

The benefits of a consumer return policy have been extensively studied in extent literature. This paper explores the potentially damaging impact of a return policy on the retailer. We develop an analytical framework and examine the economic impact of consumer return among consumers, retailer and supply chain. We distinguish three network-externality (NE) cases: no network externality, fixed network-externality and variable network-externality contingent on return amount to discuss the retailer’s selling price, refund and inventory policies. Our analysis derives the optimal policies and shows that they take the form of contingence model in which the policies depend on consumer initial return and NE return. We also examine the influence of the consumer return NE effect on buy-back contracts of the supply chain and show that while the traditional buy-back contract fails to coordinate the supply chain, the NE effect does not render the differentiated buy-back contract less effective. Finally, we extend our study to a heterogeneous consumer case.     

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.     

Operational and environmental decisions for a two-stage supply chain under vendor managed consignment inventory partnership

Supply-chain-based organisations are nowadays facing intense pressure to abide to environmental regulatory requirements while they are striving to be responsive to customers’ needs at the least cost possible. As supply chain activities are among the top contributors to carbon emissions, several recent research works have investigated the impact of carbon regulation policies on economic and environmental supply chain performance. This paper presents integrated economic and environmental models for the one-vendor one-buyer supply chain problem under a vendor managed consignment inventory (VMCI) arrangement. Through the developed models, we study the impacts of two carbon reduction policies, namely carbon cap and carbon tax policies, on supply chain wide costs and carbon emissions. We first provide a much simpler and more compact formulation for the basic single-vendor single-buyer supply chain under VMCI agreement. We also present an environmental-based VMCI model where reduction of carbon footprint is considered as the only objective function. We then extend these two basic models to include each of the two carbon emissions reduction policies. We identify structural properties for the optimal solutions of the two hybrid economic and environmental models and propose algorithms to generate optimal solutions. The results of the computational experiments reveal that the implementation of carbon reduction policies, through carbon cap and carbon tax, may call for the adjustment of the vendor’s production and buyer’s delivery quantities to reduce carbon footprint without significantly increasing the operational costs.     

Determination of the optimal degree of information sharing in a two-echelon supply chain

Information sharing is beneficial for supply chains, but often has marginally decreasing impacts on profit due to the costly expense of collecting more detailed information. This study aims to determine the optimal degree of information sharing with consideration of the trade-off between the cost of collecting information and the benefits gained by utilising it to enhance the profit of a two-echelon supply chain. Based on the analytical results, the profit that the supplier gains from information sharing can stem from the decrease in inventory cost after having more accurate information about demand. Furthermore, the impacts that the cost of collecting information has on the optimal degree of information sharing are investigated, and the results show that the optimal degree of information sharing is positively correlated to the correlation of successive market demand, that is, when the demand for successive periods is more correlated, information sharing becomes more valuable, and hence the optimal degree of information sharing increases.     

Dynamic mutual adjustment search for supply chain operations planning co-ordination

Operational planning is an activity carried out by all manufacturing and logistical companies. Its co-ordination with supply chain partners aims at synchronising resources utilisation in order to minimise inefficiencies, such as unnecessary inventory holding, or in order to improve revenue through better resource utilisation. It is a rather complex process as partners have different objectives and information asymmetry is part of any effort to find good co-ordination solutions. Furthermore, because supply chains evolve in a dynamic and uncertain environment, once a co-ordination of operations plans is achieved, input data, such as forecasts or resources’ status, can change and affect on hand plans. These dynamic changes not only require updating the plan that is directly affected by the changes, but it also requires the adjustment of all plans that are part of the same co-ordination solution (Stadtler, H. 2009. A framework for collaborative planning and state-of-the-art. OR Spectrum, 31 (1), 5–30). Therefore, the development of a practical co-ordination approach should be capable of dealing with these dynamic changes. This paper proposes a dynamic mutual adjustment search heuristic, which can be used to co-ordinate the operations plans of two independent supply chain partners, linked by material and non-strategic information flows. Computational analysis shows that the proposed approach produces a win-win strategy in the context of two supply chain partners, and improves the results of upstream planning in each planning cycle, and also improves the fairness of revenue sharing when compared to optimal centralised planning.     

Study on the decision-making and coordination of an e-commerce supply chain with manufacturer fairness concerns

The decision-making and coordination of an e-commerce supply chain (ECSC) with manufacturer fairness concerns by incorporating the e-commerce platform into the decision-making process is studied in this paper. An ECSC composed of a single manufacturer and a single e-commerce platform is developed, and the optimal decisions for three scenarios are investigated, namely, a decentralised decision-making model without consideration of fairness concerns, a decentralised decision-making model considering manufacturer fairness concerns, and a centralised decision-making model. Then, a comparative analysis of the optimal decisions of the different models is conducted. On this basis, a coordination mechanism for the decentralised decision-making models is further proposed, and finally, a numerical analysis is employed to verify the conclusions. The research shows that the e-commerce platform, although it is the dominant party, obtains less profit than the manufacturer due to the unique operation characteristics of the ECSC. The sales price, service level, and profit of the ECSC are maximised in the centralised decision-making model, and they are not affected by the commission rate. The sales price, service level and profit of the decentralised decision-making model that considers manufacturer fairness concerns are inferior to those for the model that considers fairness concerns, indicating that manufacturer fairness concerns reduce system efficiency. In addition, a ‘cost sharing joint commission’ contract can be used to coordinate an ECSC.     

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.     

A blockchain-based approach for a multi-echelon sustainable supply chain

Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.     

Coordinating a supply chain under demand and cost disruptions

In this paper, we investigate the coordination of a supply chain consisting of one manufacturer and n Bertrand competing retailers under disruptions of market demand and production cost. We present a coordination model of a supply chain under normal scenarios. Our findings demonstrate that the coordination scheme designed for the initial production plan should be revised when disruptions of market demand and production cost occur. To resolve this issue, we consider the possible deviation costs caused by disruptions and propose optimal decision models for different disruptions under centralised decision-making. We present an improved revenue-sharing contract model to coordinate the decentralised supply chain under disruptions. The proposed models are then further analysed through numerical examples.     

Optimal pricing strategy for the perishable food supply chain

This research investigates the optimal pricing strategy for the perishable food supply chain. Using the setting of a two-echelon supply chain including a supplier and a retailer, we apply the game theory approach to derive the equilibriums for both a single pricing strategy and a two-stage pricing strategy. Through a comparison of the equilibriums, we explore how the two pricing strategies affect the supply chain’s decisions and supplier’s and retailer’s performance individually and collectively. The results of the analysis show that the optimal choice of pricing strategy depends on the price markdown cost and its relationship with the two critical thresholds that are determined by a combination of factors including the potential market size, the price and quality sensitivity factors, the initial quality, the unit product cost, and the quality deterioration rate.     

Analytical foundations for development of real-time supply chain capabilities

The emergence of real-time supply chain visibility technologies has raised challenges for organisations in developing the required management capabilities required to exploit enhanced visibility. The convergence of cloud computing, mobile technology, distributed computing, and data integration technologies has enabled managers for the first time to have real-time visibility of material flows in end to end supply chains, enhancing their ability to identify bottlenecks and disruptions of material flows anywhere in their network. To effectively harness these technologies, a new set of managerial decision-making capabilities as well as enhanced data governance disciplines will be required. In this research, we employ organisational information processing theory to explore the relationship of analytical capabilities, data quality, reporting quality, and real-time data capabilities on supply chain performance. Our research model suggests that the benefits of real-time information technologies are dependent on quality reporting and managerial analytical strengths to derive supply chain benefits. The implications for managerial applications and research are further described based on these findings.     

Collaborative model for a two-echelon supply chain with uncertain demand under carbon tax policy

Consideration of carbon policies while optimizing supply chain operations has become imperative as governments and regulatory bodies throughout the world have implemented different carbon policies to reduce emissions of greenhouse gasses, especially CO₂. “Carbon tax” is one of the major carbon policies, initiated by several governments to curtail emissions. In this study, we have considered this policy to optimize the total expected cost (TEC) of a two-echelon integrated supply chain with stochastic demand, where both backorders and lost sales are permitted. An unconstrained mixed integer non-linear programming (MINLP) problem is formulated and further solved to find the optimal production rate, order quantity, number of shipments and reorder point while minimizing the TEC. Emissions from all the major sources such as production, inventory and transportation have been taken into consideration. It is assumed that the emission from production is a function of production rate, and emission from transportation depends on payload and vehicle type. This study will help organizations to reduce cost and emissions, and regulatory bodies to decide proper tax rate on carbon emission.     

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.     

供应链订货与营销渠道协调的主从对策模型

研究了供应链订货与营销渠道的协调问题,考虑了零售商具有订货成本缩减和营销投资成本,建立了供应链订货与营销渠道协调的Stackelberg主从对策模型.这一模型中,主方零售商具有产品零售价格和投资决策权,从方供应商具有产品批发价格决策权.分析了零售商四种投资策略,针对每种投资策略下的协调模型进行了数值仿真,结果表明在零售商订货成本缩减和营销之间进行投资协调能够同时增加零售商和供应商利润.     

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.     

The bullwhip effect in hybrid supply chain

As the service is becoming the strategic preference in the manufacturing industry, more and more manufacturing companies provide customers with total solutions by integrating services into their core product offerings, which is usually implemented in so-called hybrid supply chain (HSC). The HSC is formed as a chain by a group of manufacturers and service providers who work together to offer total solutions to customers. In HSC, customers’ responses to variable service levels and the interaction between inventory strategy and service capacity strategy have a great impact on supply chain instability, which represents an important concern in supply chain research. To tackle this problem, we establish a system dynamics model, by taking the HSC for an elevator company in China as an example. Firstly, we analyzed the oscillation characteristics of service flow and product flow. Then, we proposed the performance metrics of bullwhip effect in HSC. Finally, based on the model, we find that the bullwhip effect of HSC could be smoothened by incorporating service capacity adjustment strategy into the inventory replenishment policy.     

The optimal technology licensing strategy under supply disruption

We study the problem of whether and how a patent-holding firm (supplier S1) should license its technology patent to a potential rival (supplier S2). If the license is given, the two suppliers both produce a critical component for their downstream manufacturer simultaneously (sequentially) when the manufacturer adopts a dual (contingent) sourcing mode. However, both suppliers face risks of complete supply disruptions. In the study, we examine how the supply risk affects S1's technology licensing willingness and under which conditions royalty or fixed-fee licensing is its optimal strategy. The results show that when the manufacturer adopts contingent sourcing, S1 is always willing to license its technology to S2 and fixed-fee licensing is the optimal strategy. However, when dual sourcing is adopted, either royalty and fixed-fee licensing could be S1's optimal licensing strategy, depending on the reliability degree of the suppliers’ productions. Our findings extend the conclusion from previous researchers about royalty and fixed-fee licensing in a Cournot duopoly model.     

An optimal ordering strategy for a third-party managed supply chain

The rapid pace of new product introduction and global sourcing of raw materials and manufacturing facilities have created a complex and fragmented supply chain. Retailers in many consumer product industries are relying on third-party supply-chain managers (SCMs) to manage the global supply chain cost-effectively with short production lead times. To meet delivery requirements, the SCM must start the production process before receiving a firm order from retailers. We assume a two-stage production process where, in stage 1, a base product is produced. In stage 2, the base product is customised. The SCM absorbs the penalties associated with over- or underestimating retailers’ demand. Hence, the SCM has to decide on (a) the optimal production quantity of the base products and (b) the number of base products to be customised without delay. We develop a profit maximisation model for this strategy using a nonlinear objective function with two decision variables and one constraint. Applying Kuhn–Tucker conditions, closed-form solutions are obtained for the two decision variables. Also, formulations are given for two additional strategies: postpone customisation of all products and produce customised products only. An example illustrates the use of our model. We also examine the impact of demand variability on the effectiveness of the three strategies. Results show that postponement may not always be the best strategy for an SCM.