Available-to-promise-based flexible order allocation in ATO supply chains

This paper presents a new available-to-promise (ATP) based order allocation model, which is different from traditional order fulfilment systems in that it considers customer priority in an assemble-to-order (ATO) supply chain environment before the order is fulfilled. First, in terms of customer priority, a pre-allocated model is proposed in order to obtain reserving production capacity ATP and reserving components ATP for each customer class. Then, two order fulfilment models are formulated: the batch order fulfilment model for processing all orders during an order reception period and the real-time order fulfilment model for making order fulfilment decisions when an order arrives immediately. In case that the available production capacity and components are not enough, the ATP searching rules are developed along four dimensions (time dimension, customer demand priority level dimension, product dimension and selling area dimension). Finally, the proposed models are illustrated through an electronic product manufacturing case. The results of the case study show that the performance of the proposed order fulfilment system is better than that of the traditional one.     

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.     

Optimal production scheduling with customer-driven demand substitution

This paper deals with the production scheduling problem with customer-driven demand substitution. We consider a manufacturing system in a make-to-stock environment which is potentially able to produce a large variety of product options (the so-called long-term product assortment) but, for reasons of capacity and operative limitations, only a subset of those options can be available in stock at the same time (the so-called short-term product assortment). In such a context, typical of fields where high-variety strategies are applied, the first-choice option of the customer could be unavailable at a certain instant of time. In that case, if production is planned by taking demand substitution issues into consideration, other options which are good substitutes will be available, thus increasing the probability that the customer chooses to substitute. The paper proposes two mixed-integer linear programming models (for both the lost sale case and the backorder case) for optimising the production schedule by jointly considering (i) capacity and production constraints, and costs on one hand, (ii) and demand substitution issues on the other hand. An extensive experimental analysis has allowed us to evaluate the models’ behaviour in a variety of operative scenarios and to draw some concluding remarks.     

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.     

Optimal order quantity and product modularity for a two-echelon returnable supply chain

This study considers a supply chain consisting of a manufacturer, a retailer, customers and a returnable and modular product with uncertain demand, in which customers return the unsatisfactory products to the retailer, and the retailer returns the unsold products to the manufacturer. We investigate the effects of the manufacturer’s refund for the retailer’s unsold products and the product modularity under the decentralised and the centralised strategies. We confirm that the order quantity and customer’s return probability both affect the optimal modularity level of the product, and that the optimal modularity level is related to the refund policy. Also, a strategic alliance between the supply chain members is more advantageous to product innovation based on modularity for a returnable chain. Finally, managerial insights and remarks are offered.     

Robust material requirement planning with cumulative demand under uncertainty

In this paper, we deal with the problem of tactical capacitated production planning with the demand under uncertainty modelled by closed intervals. We propose a single-item with backordering model under small uncertainty in the cumulative demand for the Master Production Scheduling (MPS) problem with different rules, namely the Lot For Lot rule and the Periodic Order Quantity rule. Then we study a general multilevel, multi-item, multi-resource model with backordering and the external demand on components for the Material Requirement Planning (MRP) problem under uncertainty in the cumulative demand. In order to choose robust production plans for the above problems that hedge against uncertainty, we adopt the well-known minmax criterion. We propose polynomial methods for evaluating the impact of uncertainty on a given production plan in terms of its cost and for computing optimal robust production plans for both problems (MPS/MRP) under the assumed interval uncertainty representation. We show in this way that the robust problems (MPS/MRP) under this uncertainty representation are not much computationally harder than their deterministic counterparts.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.     

Supply chain resilience for single and multiple sourcing in the presence of disruption risks

This paper investigates the use of sourcing strategies to achieve supply chain resilience under disruptions. The coping strategies considered are single and multiple sourcing, backup supplier contracts, spot purchasing, and collaboration and visibility. Collaboration and visibility, which affect suppliers’ recovery capabilities and a buyer’s warning capability, have not been similarly modelled in the past. A scenario-based mathematical model is developed such that it considers objectives under uncertainties including disruption risks and operational risks. A broad numerical study examines its output for various risk attitudes in a decision-maker, ranging from risk neutral to risk averse. The sensitivity of procurement strategies to other key parameters such as recovery and warning capabilities is examined. One of the major findings is that buyer’s warning capability plays a vital role in enhancing supply chain resilience. We seek to build on these efforts to further support disruption planning and mitigation and to obtain a deeper understanding of the relationship between supply chain characteristics and resilience.     

Storage assignment and order batching problem in Kiva mobile fulfilment system

This article studies the storage assignment and order batching problem in the Kiva mobile fulfilment system. The storage assignment model aims to decide which product to put in which pod to maximize the product similarity and the order batching model aims to minimize the number of visits of pods. To solve the order batching problem, a heuristic is proposed, where a batch schedule is initialized with the objective of maximizing the order association or minimizing order alienation and improved by variable neighbourhood search. Computational experiments are conducted to verify the performance of the proposed model and algorithm.     

The impact of the customer order decoupling point on type and level of supply chain integration

Literature suggests that more supply chain (SC) integration increases of SC performance. However, recent research shows that contextual factors affect the effectiveness of SC integration efforts. Specifically, the location of the customer order decoupling point (CODP) might be such a factor, but there is limited empirical evidence. This study explores the impact of the location of the CODP on SC integration. It empirically investigates upstream, internal and downstream SC integration efforts in twelve metal parts producing Dutch companies to offer a comprehensive view of the effects of the location of the CODP on SC integration. Our results show a clear relationship between SC integration and the location of the CODP. Specifically, make-to-order (MTO), assemble-to-order (ATO) and make-to-stock (MTS) companies show relatively high levels in upstream, internal and downstream SC integration, respectively. Moreover, MTO companies mainly share forecast information and engage in joint R&D with their suppliers, ATO companies focus on internal SC integration using information systems and planning, while MTS companies interact with their customers intensively to exchange forecast information. Our study adds to the insight on the application of SC integration in different situations and offers initial evidence for the effects of the location of the CODP on SC integration.     

具有产品再制造的闭环供应链动态运作模型

考虑了一类同时具有再分销、再制造和再利用的闭环供应链,并建立了其动态运作模型.供应链由一个制造商和一个供应商组成,废旧产品的回收及对废旧产品的再处理均由制造商完成.采用离散概率分布描述最终产品废旧的可能性,闭环供应链的运作是动态的且满足诸如供应链成员之间协调、各成员运作收益最大等多个目标.设计了一个数值算例验证模型的有效性,并就回收率对闭环供应链的运作性能的影响进行了分析.结果表明,闭环供应链的整体运作性能随着回收率的增大而增加.     

Capacity investment and the value of operational flexibility in manufacturing systems with product blending

A distinct feature of process industries such as food, chemical and consumer packaged goods is the blending of intermediates into finished goods. In the context of such manufacturing systems the levels of different inputs that can be blended to process a final good define the range of flexibility. Likewise, the cost for using (blending) different inputs defines the mobility element of flexibility. In this paper, we investigate capacity investment and the value of flexibility in the presence of such product blending constraints. We are motivated by recent case studies of food manufacturers, in particular, those manufacturers that seek to increase flexibility via blending of intermediates. We analyse stochastic programs under demand uncertainty of such manufacturing systems. We provide analytical insights into trade-offs when range and mobility are interdependent. Our analytical work gives structural insights into subtle complementarity and substitution effects between dedicated and shared resources in the presence of blending. We analytically show that there is a degradation in the cost performance of such systems with an increase in correlation. We characterise the optimal blending fraction that balances the benefits of higher range with higher costs (lower mobility). Our numerical work shows that a moderate level of blending can significantly improve flexibility and that well-known guidelines for designing limited flexibility change in the presence of blending. For example, blending, even if optimally designed, weakens the appeal of chaining configurations. Overall our work guides resource configuration in industries where product blending is an integral part of the production process.     

A two objective optimisation model for order splitting among parallel suppliers

To correctly split an order among parallel suppliers is one of the most important ways to improve the agility and competitiveness of a supply chain. For this order splitting problem, an evaluation criterion of production load equilibrium among parallel suppliers is introduced and a two objective order splitting model is developed to minimise the comprehensive cost and balance the production loads among the selected suppliers. The procedure of the suppliers’ selection is proposed and non-dominated sorting genetic algorithm (NSGA-II) is applied to find the feasible solution set of Pareto. The simulation results indicate that the proposed model and algorithm is capable of obtaining satisfactory solutions.     

基于非线性控制理论的突发需求订货策略研究

基于非线性控制理论,建立生产商、分销商和零售商在内的三阶供应链动态订货模型,使用混沌理论的李雅普诺夫指数度量突发需求扩散产生的订货量、库存量和缺货量不确定性.通过仿真软件Simulink比较了突发需求情景下,采用APIOBPCS订货策略和OUT订货策略时的系统不确定性变化.研究发现:在降低突发需求产生的库存量、订货量和...     

A multi-objective optimisation approach for order management: incorporating activity-based costing in supply chains

Most of the supply chain order management decision making models proposed in the literature are based mainly on the material flow and capacity constraints without any consideration to the profitability factor. In this paper, we develop a multi-objective mixed-integer programming (MIP) model which considers profitability in order to effectively manage order acceptance decisions in supply chains, subject to capacity constraints by using activity-based costing (ABC). While there are a numbers of decision-making models in literature integrating ABC in supply chains, this study expands the previous models with a more customer-oriented approach. The proposed model fulfils a desirable amount of orders completely and accepts selective number of orders partially with an objective of minimising the amount of residual capacity and increasing the profitability.     

Customer segmentation,allocation planning and order promising in make-to-stock production

Modern advanced planning systems offer the technical prerequisites for an allocation of “available-to-promise” (ATP) quantities—i.e. not yet reserved stock and planned production quantities—to different customer segments and for a real time promising of incoming customer orders (ATP consumption) respecting allocated quota. The basic idea of ATP allocation is to increase revenues by means of customer segmentation, as it has successfully been practiced in the airline industry. However, as far as manufacturing industries and make-to-stock production are concerned, it is unclear, whether, when, why and how much benefits actually arise. Using practical data of the lighting industry as an example, this paper reveals such potential benefits. Furthermore, it shows how the current practice of rule-based allocation and consumption can be improved by means of up-to-date demand information and changed customer segmentation. Deterministic linear programming models for ATP allocation and ATP consumption are proposed. Their application is tested in simulation runs using the lighting data. The results are compared with conventional real time order promising with(out) customer segmentation and with batch assignment of customer orders. This research shows that—also in make-to-stock manufacturing industries—customer segmentation can indeed improve profits substantially if customer heterogeneity is high enough and reliable information about ATP supply and customer demand is available. Surprisingly, the choice of an appropriate number of priority classes appears more important than the selection of the ATP consumption policy or the clustering method to be applied.     

An empirical study of impacts of production mix,product route efficiencies on operations performance and profitability: a reverse logistics approach

This research studies the impact of two reverse logistics business strategies on profitability of the firm through operations management (OM). The study is employed on scrap steel industry. The first strategy is production mix efficiency (PME), which is involved in the process of producing goods. The second strategy is product route efficiency (PRE), which engages in the transportation of goods. Our finding indicates that OM alone does not have a positive impact on profitability. However, the two strategies have a positive effect on profitability, which provides a potential answer to firms trying to improve profitability.     

Interdependent order allocation in the two-echelon competitive and cooperative supply chain

In this paper, we consider an order allocation problem in a two-echelon supply chain with multiple suppliers and multiple demanders. The orders from the demanders are interdependent in terms of execution sequence. We consider both the competition and cooperation relationships between the suppliers and demanders. We provide formal definition for the order allocation problem and propose a negotiation mechanism which includes a two-stage negotiation protocol and two heuristic negotiation algorithms. Different negotiation strategies are proposed for the demanders and suppliers to resolve the order interdependency and competition conflict. An automated negotiation approach is introduced to implement the negotiation mechanism. The computational experiments show that orders under different supply chain contexts can be allocated with high success rate. We also numerically compare the influence of different negotiation strategies and investigate the interaction of conflict resolutions.     

单周期随机需求下供应链库存协调机制设计

研究了单周期随机需求条件下两级供应链的库存协调机制设计问题.建立了基于弹性订货策略的供应链库存风险共担机制,并通过算例验证了弹性订货策略在供应链库存协调中的有效性.研究结果表明,在供应链上下游无合作时,需方承担全部库存风险,其个体理性的决策无法实现供应链的整体优化,而如果双方实施弹性订货策略,分担库存风险,则可以实现供应链的Pareto优化.     

The impact of dual-market on supply chain configuration for new products

Given a firm’s supply chain network, the key objective of supply chain configuration (SCC) is to determine a subset of supply chain partners to be involved in development, sourcing, production, distribution and support of a new product at the highest level of efficiency and expected responsiveness. Current literature on SCC realises the importance of considering the demand dynamics associated with the new product diffusion (NPD). However, these studies assume one-segment market for new products, a single homogenous consumer segment. Recent research in marketing indicates that such simplification might be fatal because a diverse and significant number of product categories may experience a dual-market structure, namely early and main markets, and generate a different demand dynamics. The objectives of this study are to: (i) develop a hybrid optimisation model, capturing both SCC decisions and the demand dynamics of dual-market NPD process; (ii) based on real-world data for a host of electronic product categories, various SCC networks and NPD demand dynamics, examine the new integrated optimisation model under one- and two-segment market; and (iii) present relevant managerial implications and guidelines for supply chain and marketing managers. Our extensive comparative computational experiment with 26 categories of consumer electronic products show that on average the relative net profit may improve significantly, when the market is considered as two-segment.