Determining end-of-life policy for recoverable products

We address a problem that arises for an original equipment manufacturer (OEM) who produces a product both in new and remanufactured forms. A remanufactured product is produced using the parts harvested from recovered products (cores) upon their disassembly, and it may contain some new parts while the excess good parts from cores are salvaged for profit. Other options are available to the OEM for handling cores that do not require disassembly. It follows that the per-unit remanufacturing cost is not constant and it may change depending on the number of recovered cores, good-part reclamation yields, and sales of remanufactured products. We present analytical results for determining an optimal solution with regard to: (i) quantity of cores to collect, (ii) end-of-life (EOL) options for the cores and (iii) product pricing of new and remanufactured products. Our analysis reveals existence of a ‘limiting part’ that dictates the number of cores to collect and a ‘key part’ that determines the number of remanufactured products to make as well as the fact that the availability of cores does not impact the EOL policy type for a product. Our analysis also enables mapping of product characteristics onto corresponding EOL policy types.     

绿色供应链管理的基本原理

人口、资源与环境三者之间的矛盾日益突显，要求制造业提高其活动与环境的相容性。绿色供应链管理是从系统的观点与集成的思想出发解决制造业与环境之间冲突的有效方式。从可持续发展的思想出发建立了绿色供应链的概念模型，分析了绿色供应链管理的目标，在此基础上探讨了绿色供应链管理的基本原理，认为共生原理、循环原理、替代转换原理与系统开放原理是实施绿色供应链管理应该遵循的基本原理。     

纸质书与电子书双渠道供应链定价与契约选择策略

为研究纸质书与电子书的定价与出版商契约选择策略,基于博弈理论构建以契约组合为联结方式的四类图书双渠道供应链模型。研究表明,纸质书与电子书价格是替代率、单位版税成本的增函数,与买断成本无关。当版税成本较小时出版商选择版税契约,否则选择买断契约;当分成比例较小时出版商选择代理契约,否则选择批发契约。图书替代率越小出版商越偏爱版税契约和代理契约,图书替代率越大出版商越偏爱买断契约和批发契约。     

A green supply chain is a requirement for profitability

Many companies are not dramatically changing to more sustainable environmental practices despite pressure from the investment community, the government and consumers. This study explores a simple model that companies can use to understand and improve supply chain sustainability practices. It applies this model in two case studies, Coca-Cola, a leader in global sustainability, and Apple, a company that has only recently started to develop a sustainability strategy. The model was developed through a review of existing research and an application of supply chain principles. The results of this study demonstrate that following this model to eliminate waste throughout the supply chain will make the supply chain more profitable. The outcomes from this study highlight the importance for every company to do so in order to stay competitive. This study is unique in the relative simplicity of its model, combined with the supporting evidence that a sustainable supply chain is the same as a supply chain that is using best practices to reduce waste.     

The effect of supply and demand uncertainties on the optimal production and sales plans for new products

When introducing a new product, firms face a hierarchy of decisions at the strategic and operational levels including capacity sizing, time to market or starting sales, initial inventory required by the product’s release time and production management in response to changes in the demand (hereafter referred to as production-sales policies). The goal of this paper was to show the importance of considering both supply and demand uncertainties in the determination of the production-sales policy which has been overlooked in the existing literature. More specifically, we test two main hypotheses: (1) ignoring supply and demand uncertainties may lead to potentially incorrect decisions; and, (2) the decision could be different if risk is used as the primary performance measure instead of the commonly used expected (mean) profit. We perform extensive experimentation with a Monte Carlo simulation model of the stochastic supply-restricted new product diffusion and use different statistical procedures, namely, the Welch’s t-test and a nonparametric double-bootstrap method to compare the average and percentiles of the profit for different policies, respectively. The results indicate that the correctness of the two hypotheses depends on the diffusion speed, consumers’ backlogging behaviour, production capacity, price and variable production and inventory costs. The findings also have important implications for managers regarding market entry time, parameter estimation, production strategy and the implementation of the proposed model.     

The impact of strategic inventory and procurement strategies on green product design in a two-period supply chain

This study analyses the impact of power structures and strategic inventory on the development-intensive and marginal-cost-intensive green product types under three procurement strategies. The results suggest that (i) in the manufacturer-Stackelberg game, the retailer retains strategic inventory to earn higher profits. The retailer's decision improves profit for the manufacturer and greening level of the product; (ii) for the marginal-cost-intensive green product, the power structures and procurement strategies cannot make any impact on the greening level and the retailer cannot build up strategic inventory under retailer-Stackelberg game; (iii) under the Nash game, the procurement decision creates conflict between the supply chain members for marginal-cost-intensive green products; (iv) if the retailer does not maintain strategic inventory or procures product in a single lot, then the manufacturer prefers to produce marginal-cost-intensive products and retailer prefers to sale development-intensive products to receive maximum profits under manufacturer-Stackelberg game. The optimal preferences are concurrent under retailer-Stackelberg game, but not under the Nash game; (v) single-period equilibrium solutions may exhibit sub-optimal characteristics, but two-period planning can lead to exemplary outcomes in the perspective of the greening level and profits of the supply chain members.     

A multi-agent architecture for reverse logistics in a green supply chain

Green supply chain issues have attracted a lot of attention in recent years with growing awareness of environmental concerns. This has drawn the considerable world-wide attention of academics and practitioners. Therefore, recycling has now become an integral component of the supply chain. Recycling of used products and the related logistics management pose a significant challenge to manufacturing industries. In order to resolve the complexity of the task, this study proposes a multi-agent architecture to handle recycling and reverse logistics issues, which have so far been neglected. It addresses the different aspects of recycling such as waste classification, recycling, logistics and reuse of products. Additionally, it also discusses how the agent communicates and acts autonomously to facilitate the efficient logistics of materials between different units. The proposed agent architecture can assist manufacturing industries in efficiently managing their green supply chain system and complex logistics issues.     

Using fuzzy analytic hierarchy process and particle swarm optimisation for balanced and defective supply chain problems considering WEEE/RoHS directives

This research explored problems concerning production and delivery in a green supply chain, and constructed an optimal mathematical model to provide solutions. This model incorporates WEEE and RoHS in EU directives for the selection of green partners when establishing a supply chain. The weight of each component is calculated by fuzzy analytic hierarchy process (fuzzy AHP). Previous studies suggested that a supply chain is a balanced system, however, in actual practice, there may be processing damages or delivering losses. Thus, such a supply chain with production loss is known as a ‘defective supply chain’. This research analysed the defective supply chain system to discuss its supplier selection, production, and distribution. It developed an optimal mathematical model for both balanced and defective models, and adopted particle swarm optimisation (PSO) to obtain solutions for both models. Finally, case studies for both models with quality solutions were discussed to confirm the efficiency and effectiveness of the proposed approach.     

When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry

The pharmaceutical industry is very important in delivering life-saving products/services to society. There are many ways for materials/products/services concerned with pharmaceuticals to influence the environment; these include improper disposal of pills/tablets by patients, expired and unused medications, improper release of drugs by pharmacies or household sewage mixed with surplus drugs. In view of this, the present work seeks to integrate green supply chain (GSC) concepts in the pharmaceutical sector in a developing economy Indian context. In so doing, managers need to determine the potential risks in adopting GSC initiatives to achieve sustainability in operational perspectives. In this sense, this work seeks to distinguish the potential risks in adopting GSC initiatives within the pharmaceutical industry. This work uses a literature review and fuzzy Delphi approach in finalising the risks. This research also uses fuzzy Analytical Hierarchy Process (AHP) for prioritisation of the risks under vague and unclear surroundings. According to the findings, cold chain technology and supply risks categories are highly prioritised. This work can assist practising managers and government authorities in effectively developing and managing GSC initiatives in line with sustainable development goals in the context of the pharmaceutical industry. Finally, a sensitivity test is applied to evaluate the stability of ranking of risks.     

Optimising replenishment policy for an integrated production inventory deteriorating model considering green component-value design and remanufacturing

This paper develops an integrated deteriorating production inventory model with green component design, remanufacturing and JIT deliveries. We provide a rigorous analysis to derive the number of deliveries, the optimal cycle time of deliveries, and the delivery sise for the integrated buyer-supplier inventory deteriorating model. Distinct from the former concept of average inventory level, our paper proposes a significantly different approach to deal with the first production batch and uses a revised method to approximate the relationship between the supplier's production and storage time. A manufacturing case example of Taiwan computer power-supply component producers is presented to illustrate the theory. It is shown that the parameters of component-value design and unit holding cost are the critical factors affecting the deteriorating inventory planning.     

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.     

商品钢筋供应链渠道长度设计研究

立足于商品钢筋经销商,以避免与渠道中下游客户的冲突和提升竞争力为目的,研究商品钢筋供应链渠道长度优化选择方法。将双层规划模型应用于商品钢筋供应链渠道长度设计之中,通过对模型解的分析,给出了商品钢材经销商在渠道长度选择中应采取的策略。结合实例,验证双层规划方法可有效地用于供应链渠道长度选择。     

A hybrid multi-agent negotiation protocol supporting supplier selection for multiple products with synergy effect

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.     

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.     

汽车制造商的零售与租赁混合渠道管理策略

在两周期设置下,将制造商占主导的零售与租赁混合渠道结构区分为独立式、冲突式和回购式三类,然后分析了租赁渠道对零售渠道的影响以及制造商相应的渠道管理策略。结果表明:对于制造商而言,回购式结构是较为稳定的渠道结构,其可以平衡零售商和租赁商的利益。     

A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling

Recycling plastic can abate the environmental pollution as well as CO₂ emissions by saving the carbon-intensive feedstock input. The uncertain carbon price places significant effects on the establishment and operation of the whole supply chain. This study develops a green supply chain model combined with geographic information system (GIS) to account for carbon price uncertainty and evaluate its effects on the closed-loop supply chain (CLSC) of plastic recycling. A two-stage stochastic programming model is constructed, in which the stochastic variable, CO₂ price is modelled as a geometric Brownian motion process. Six scenarios are designed with respect to price expectation and volatility. A case study is performed with the GIS information of the plastic supply chain in Zhejiang province, China. The results illustrate that triggering the establishment of reverse logistics requires a carbon price threshold significantly beyond the current level. Lower price volatility would facilitate the decision-making of investment into the reverse logistics. Mechanisms to alleviate the market variation shall be introduced. A sound market condition is desired to obtain the optimal balance that encourages the CLSC without creating extra pressure on the firms. The proposed modelling framework can be easily applied to other sectors with similar characteristics.     

A hybrid optimisation approach to configure a supply chain for new product diffusion: a case study of multiple-sourcing strategy

Configuring a supply chain for a new product is a challenging task due to the lack of historical demand data and the dynamic/uncertain nature of the new product diffusion process. An integrated supply chain configuration (SCC) and new product diffusion (NPD) model is developed to explicitly account for the impact of demand dynamics during a new product's diffusion on an optimal supply chain configuration. Our hybrid NPD-SCC model allows a manufacturer to source from multiple suppliers, vendors or modes for its supply chain entities. Such a multiple-sourcing approach not only helps the manufacturer to diversify its pool of suppliers and maintain bargaining power, but also builds redundancy into the supply chain to hedge against potential demand surge and supply disruption during the new product life cycle. Through a case study and a comprehensive computational study, we find that although the single-sourcing solution is able to achieve lower unit-manufacturing cost (UMC), the multiple-sourcing approach is superior to single-sourcing on the overall supply chain performance in the environment with random supply disruptions. By building-in redundancy as multiple suppliers and modes, the resultant supply chain has less chance of being disrupted and achieves higher overall profit on average. We also draw several other managerial insights closing the gap between some supply chain operations and marketing strategies.     

Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor

A semiconductor distributor that plays a third-party role in the supply chain will buy diverse components from different suppliers, warehouse and resell them to a number of electronics manufacturers with vendor-managed inventories, while suffering both risks of oversupply and shortage due to demand uncertainty. However, demand fluctuation and supply chain complexity are increasing due to shortening product life cycle in the consumer electronics era and long lead time for capacity expansion for high-tech manufacturing. Focusing realistic needs of a leading distributor for semiconductor components and modules, this study aims to construct a UNISON framework based on deep reinforcement learning (RL) for dynamically selecting the optimal demand forecast model for each of the products with the corresponding demand patterns to empower smart production for Industry 3.5. Deep RL that integrates deep learning architecture and RL algorithm can learn successful policies from the dynamic and complex real world. The reward function mechanism of deep RL can reduce negative impact of demand uncertainty. An empirical study was conducted for validation showing practical viability of the proposed approach. Indeed, the developed solution has been in real settings.     

A hierarchical model for optimal supplier selection in multiple sourcing contexts

This paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e. optimal supplier selection. We present a hierarchical extension of the data envelopment analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier according to some criteria proposed by the buyer. Second, the well known technique for order preference by similarities to ideal solution (TOPSIS) is applied to rank the maximally efficient suppliers given by the previous step. Third and finally, a linear programming problem is stated and solved to find the quantities to order from each maximally efficient supplier in the multiple sourcing context. The presented approach is able to straightforwardly discern between efficient and inefficient partners, avoid the confusion between efficient and effective suppliers and split the supply in a multiple sourcing context. The hierarchical model is applied to the supply of a C class component to show its robustness and effectiveness, while comparing it with the DEA and TOPSIS approaches.     

A fuzzy goal programming approach for green supply chain optimisation under activity-based costing and performance evaluation with a value-chain structure

Supply chain operation with sustainable consideration has become an increasingly important issue in recent years. However, the decision framework with integrated costing and performance evaluation for green supply chain (GSC) has not been well developed so far in the literature. For this reason, this paper is aimed to propose a fuzzy goal programming (FGP) approach that integrates activity-based costing (ABC) and performance evaluation in a value-chain structure for optimal GSC supplier selection and flow allocation. The FGP approach is particularly suitable for such a decision model which includes flexible goals, financial and non-financial measures, quantitative and qualitative methods, multi-layer structure, multiple criteria, multiple objectives, and multiple strategies. An activity-based example of structural GSC with relevant costs and performances is presented for computing the composite performance indices of the GSC suppliers. A green supply chain of a mobile phone is used as an illustrative case. Several objective structures and their results are compared. The sensitivity analyses show that pure maximisation of financial profit can achieve the highest profit level, which also has the largest Euclidean distance to the multiple aspiration goals. In order to determine the final objective structure, an analytic hierarchy process (AHP) is used. This paper provides a new approach to assess and control a complex GSC based on value-chain activities, and obtain a more precise solution. The establishment of this GSC model not only helps decision-makers to monitor GSC comprehensive performance but also can facilitate further improvement and development of GSC management.