基于遗传算法的三级逆向物流网络设计模型研究

建立初始回收点以方便客户、提高回收速度以及建立集中回收中心以负责产品的收回、分拣并统一运送到相应的生产商或分销商修理地点是一种节约、有效的多层次产品回收模式。本文在即存研究基础之上,加入了考虑初始点回收成本、回收产品中再销售品的收益和可再利用品的收益等变量,提出了能够优化连接客户、集中回收中心和生产商三级逆向物流网络数学模型,最后灵敏度分析表明遗传算法对于求解这类问题是一种有效的方法。     

The Impact of Product Returns and Retailer's Service Investment on Manufacturer's Channel Strategies*

We study the distribution channel decision of a manufacturer who considers whether to add an online channel (direct channel) to its brick‐and‐mortar retailer (indirect channel). The retailer faces the opportunity to invest in store assistance to help consumers choose products and thus reduce product returns. Special attention is given to the impact of product returns and retailer's store assistance investment on manufacturer's dual channel decision. We examine conditions under which the manufacturer uses dual channels and how various relevant factors affect its channel decision under two settings, depending on whether the retailer has its own online store or not. When the retailer does not have its online store, we find that (i) the addition of the direct channel raises the wholesale price; (ii) the direct channel addition hurts the retailer if the nonreplacement rate is low; (iii) the manufacturer has a lower incentive to add the direct channel when the retailer's service cost is lower or its returns reduction rate from service investment is higher; and (iv) the manufacturer should treat its own returns handling cost as a key factor in its channel structure decision. In addition, when the retailer operates an online store, we find that the manufacturer may have an incentive to add a direct channel such that both firms own direct channels.     

供应链中基于信息更新的订货时间及价格联合决策研究

文章考虑在信息可更新的情况下,由一个制造商和一个零售商组成的供应链中订货时间及价格的联合决策问题.在模型中,制造商为零售商提供多次订货时间选择及相应的订货价格,而零售商可以在销售季节开始前自由选择订货时间并享受相应的价格.文章以不同订货时间对信息更新程度的影响为着眼点,将订货时间作为内生决策变量,突破了已有文献中仅限于两次订货时间选择的局限,分别从集中决策和分散决策两个角度建立供应链节点企业的利润模型,并在分散决策情况下引入收益共享契约,寻找帕累托改进.最后通过数值试验证明了该模型的有效性.     

Models for closed-loop supply chain with trade-ins

Three kinds of decision models for closed-loop supply chain (CLSC) with trade-ins are developed in this paper, including the centralized collection (Model C), the retailer collection (Model R), and the manufacturer collection (Model M). By analyzing these models, we argue that there are three types of optimal collection strategies, namely, no collection, partial collection, and full collection. We provide conditions under which one of these three collection strategies is optimal for different supply chain models. By comparing the impact of trade-ins on these different supply chain models, we find that only when the direct net value of a used product derived from the trade-ins for the whole CLSC system including the consumers is high enough can trade-in strategy be adopted to stimulate consumer demand and improve the manufacturer׳s and retailer׳s profit. Based on the life-cycle assessment method, we find that when the marginal effect of the product on environment in the continue-to-use phase is more significant than in other phases, trade-ins can promote the environmental performance of the CLSC system. Further, by comparing the optimal solutions for the different models, we find that one collection model may dominate the others in terms of the economic performance of the involved parties. Specifically, Model M dominates Model R in terms of the profits of the manufacturer and the profits of the whole supply chain; Model R dominates Model M in terms of retailer׳s profit; and Model R dominates all other models in terms of environmental performance.     

加工能力受限的单机干扰管理研究

针对单机环境下最小化加权折扣加工时间和的排序问题,研究如何应对可预见的干扰事件。由于干扰事件使得机器加工能力受限,初始最优加工时间表不再可行,采用外包的方式来进行干扰管理。构建了排序模型,同时考虑原目标和与初始计划偏离的扰动目标,选择外包工件集并对所有工件进行重排序。为了求解得到的双目标排序问题,基于理想点法设计了一种动态规划算法和量子遗传算法相结合的算法。最后通过一个数值算例说明,该排序模型对于求解加工能力受限的单机干扰管理问题是有效的。     

Designing Efficient Infrastructural Investment and Asset Transfer Mechanisms in Humanitarian Supply Chains

We analyze the efficacy of different asset transfer mechanisms and provide policy recommendations for the design of humanitarian supply chains. As a part of their preparedness effort, humanitarian organizations often make decisions on resource investments ex ante because doing so allows for rapid response if an adverse event occurs. However, programs typically operate under funding constraints and donor earmarks with autonomous decision‐making authority resting with the local entities, which makes the design of efficient humanitarian supply chains a challenging problem. We formulate this problem in an agency setting with two independent aid programs, where different asset transfer mechanisms are considered and where investments in resources are of two types: primary resources that are needed for providing the aid and infrastructural investments that improve the operation of the aid program in using the primary resources. The primary resources are acquired from earmarked donations. We show that allowing aid programs the flexibility of transferring primary resources improves the efficiency of the system by yielding greater social welfare than when this flexibility does not exist. More importantly, we show that a central entity that can acquire primary resources from one program and sell them to the other program can further improve system efficiency by providing a mechanism that facilitates the transfer of primary resources and eliminates losses from gaming. This outcome is achieved without depriving the individual aid programs of their decision‐making autonomy while maintaining the constraints under which they operate. We find that outcomes with centralized resource transfer but decentralized infrastructural investments by the aid programs are the same as with a completely centralized system (where both resource transfer and infrastructural investments are centralized).     

Why adding firm value with a put feature in debt contracts is better than renegotiation

In this paper, we analyze the ability of putable debt to add firm value. To stress the impact of a put feature, we compare the resulting optimal firm values and capital structures to those of a firm with straight debt that can be renegotiated. For this purpose, we consider a time-independent firm value model with tax-deductibility of coupon payments, bankruptcy costs in the case of a default, and dynamic restructuring. We find that a put right can always be designed so that a put is enforced for low asset values but the bond remains alive for high asset values. The optimal firm value arising from this type of equilibrium strategy is remarkable for several reasons: The optimal firm value under putable debt is always higher than under straight debt even under renegotiation with arbitrary negotiation power of debt and equity holders. Moreover, the optimal firm value under putable debt always benefits from higher bankruptcy costs, while the optimal firm value under straight debt suffers. Accordingly, a higher volatility of asset value returns can be favorable for a high firm value under putable debt, while it always destroys value of a firm with straight debt.     

Optimal Policies for Perishable Products When Transportation to Export Market Is Disrupted

We consider a problem where a firm produces a variety of fresh products to supply two markets: an export market and a local market. A public transportation service is utilized to deliver the products to the export market, which is cheap, but its schedule is often disrupted severely. Each time this happens, the firm faces the following questions. (i) For a product that has been finished and is waiting for delivery to the export market, should it continue to wait, at an increasing risk of decay, and when should the waiting be terminated and the product be put to the local market? (ii) For a product that has not been finished, should its processing be postponed, so as to reduce the loss from decay after its completion? (iii) What is the best sequence to process the remaining products, according to the information available? We develop, in this study, a model to address these and other related questions. We find optimal policies that minimize the total expected loss in both the make‐to‐order and make‐to‐stock production systems, respectively. For each finished product, we reveal relationships among the desirable waiting time, the price at the local market, and the decaying cost. For unfinished products, we find the optimal start times and processing sequence. Numerical experiments are also conducted to evaluate the optimal policies.     

Value of Information in Closed Loop Supply Chains

We explore the value of information (VOI) in the context of a firm that faces uncertainty with respect to demand, product return, and product recovery (yield). The operational decision of interest in matching supply with demand is the quantity of new product to order. Our objective is to evaluate the VOI from reducing one or more types of uncertainties, where value is measured by the reduction in total expected holding and shortage costs. We start with a single period model with normally distributed demands and returns, and restrict the analysis to the value of full information (VOFI) on one or more types of uncertainty. We develop estimators that are predictive of the value and sensitivity of (combinations of) different information types. We find that there is no dominance in value amongst the different types of information, and that there is an additional pay‐off from investing in more than one type. We then extend our analysis to the multi‐period case, where returns in a period are correlated with demands in the previous period, and study the value of partial information (VOPI) as well as full information. We demonstrate that our results from the single period model (adapted for VOPI) carry‐over exactly. Furthermore, a comparison with uniformly distributed demand and return show that these results are robust with respect to distributional assumptions.     

Lot Sizing for Optimal Collection and Use of Remanufacturable Returns over a Finite Life‐Cycle

Reverse supply chains process used product returns to recover value by re‐processing them via remanufacturing operations. When remanufacturing is feasible, the longer the return flows are delayed during the active (primary) market demand period of the product, the lower the value that can be recovered through these operations. In fact, in order to recover the highest value from remanufactured products, the collection rates, return timings, and reusability rates should be matched with the active market demand and supply. With these motivations, this paper is aimed at developing analytical models for the efficient use of returns in making production, inventory, and remanufacturing decisions during the active market. More specifically, we consider a stylistic setting where a collector collects used product returns and ships them to the manufacturer who, in turn, recovers value by remanufacturing and supplies products during the active market demand. Naturally, the manufacturer's production, inventory and remanufacturing decisions and costs are influenced by the timing and quantity of the collector's shipments of used product returns. Hence, we investigate the impact of the timing of returns on the profitability of the manufacturer‐collector pair by developing system‐wide cost optimization models. Analyzing the properties of the optimal shipment frequency, we observe that the fastest reverse supply chain may not always be the most efficient one.     

Alpha as Ambiguity: Robust Mean‐Variance Portfolio Analysis

We derive the analogue of the classic Arrow–Pratt approximation of the certainty equivalent under model uncertainty as described by the smooth model of decision making under ambiguity of Klibanoff, Marinacci, and Mukerji (2005). We study its scope by deriving a tractable mean‐variance model adjusted for ambiguity and solving the corresponding portfolio allocation problem. In the problem with a risk‐free asset, a risky asset, and an ambiguous asset, we find that portfolio rebalancing in response to higher ambiguity aversion only depends on the ambiguous asset's alpha, setting the performance of the risky asset as benchmark. In particular, a positive alpha corresponds to a long position in the ambiguous asset, a negative alpha corresponds to a short position in the ambiguous asset, and greater ambiguity aversion reduces optimal exposure to ambiguity. The analytical tractability of the enhanced Arrow–Pratt approximation renders our model especially well suited for calibration exercises aimed at exploring the consequences of model uncertainty on equilibrium asset prices.     

Quick response and supply chain structure with strategic consumers

This work explores the impact of quick response on supply chain performance for various supply chain structures with strategic customer behavior. By investigating pricing and inventory decisions in decentralized supply chains under revenue-sharing contracts and in centralized supply chains, we study the performance of four various systems and compare the value of quick response in different supply chain structures. The results show that if the extra cost of quick response is relatively low, the value of quick response would be greater in centralized systems than in decentralized systems. On the other hand, if the extra cost is high, decentralized supply chains reap more incremental profits from adopting quick response. We also find that revenue-sharing contracts enable a decentralized supply chain to outperform a centralized supply chain, but only allow limited flexibility of allocating total profits between a manufacturer and a retailer.     

Kapitalmarktreaktionen auf Personalabbauprogramme: Welchen Einfluss haben Motiv,Umfang und Freiwilligkeit?

This study examines the effects of layoff announcements on the market value of German listed companies. Analyzing 136 announcements being published between 2000 and 2009, the results show marginal abnormal returns but high variance indicating that the market reaction might depend on specific characteristics. As potential determinants we particularly discuss the reasons for layoff, the size of layoff and the voluntariness of layoff. We find that reactive reasons like plant closures have a negative impact on shareholder value whilst active reasons like cost improvements enhance shareholder value. The size of layoff tends to induce negative effects. A voluntary layoff announcement however increases the value of a firm. Furthermore, we find a positive relationship between abnormal returns and human capital intensity and a negative one with both the manufacturing industry membership and financial leverage. In addition, the regression model extends prior literature since its coefficient of determination exceeds those in Anglo-American studies.     

易腐性产品运输设施选择博弈

易腐性产品的价值会随着时间的流逝而逐渐损失,多个客户可以联合使用某种运输设施时,如何对费用进行公平且稳定的分摊是合作能否进行的基础.把易腐性产品的损失价值和运输费用之和作为总费用,进而将易腐性产品的运输设施选择的费用分配问题构造成运输设施选择合作博弈,证明了在易腐性产品负指数价值损失的情况下,运输设施选择博弈的核心非空,且为凹博弈,并讨论了解的特征.论文还证明具有附加运输费用的运输设施选择博弈的核心非空,分析了核心与线性规划松弛的对偶最优解之间的关系.论文对有约束设施选择博弈进行了分析,并提出了进一步研究的方向.     

Managing stochastic demand in an Inventory Routing Problem with transportation procurement

We study an Inventory Routing Problem in which the supplier has a limited production capacity and the stochastic demand of the retailers is satisfied with procurement of transportation services. The aim is to minimize the total expected cost over a planning horizon, given by the sum of the inventory cost at the supplier, the inventory cost at the retailers, the penalty cost for stock-out at the retailers and the transportation cost. First, we show that a policy based just on the average demand can have a total expected cost infinitely worse than the one obtained by taking into account the overall probability distribution of the demand in the decision process. Therefore, we introduce a stochastic dynamic programming formulation of the problem that allows us to find an optimal policy in small size instances. Finally, we design and implement a matheuristic approach, integrating a rollout algorithm and an optimal solution of mixed-integer linear programming models, which is able to solve realistic size problem instances. Computational results allow us to provide managerial insights concerning the management of stochastic demand.     

The Value of Quality Grading in Remanufacturing

In this paper we consider a tactical production‐planning problem for remanufacturing when returns have different quality levels. Remanufacturing cost increases as the quality level decreases, and any unused returns may be salvaged at a value that increases with their quality level. Decision variables include the amount to remanufacture each period for each return quality level and the amount of inventory to carry over for future periods for both returns (unremanufactured), and finished remanufactured products. Our model is grounded with data collected at Pitney‐Bowes from their mailing systems remanufacturing operations. We derive some analytic properties for the optimal solution in the general case, and provide a simple greedy heuristic to computing the optimal solution in the case of deterministic returns and demand. Under mild assumptions, we find that the firm always remanufactures the exact demand in each period. We also study the value of a nominal quality‐grading system in planning production. Based on common industry parameters, we analyze, via a numerical study, the increase in profits observed by the firm if it maintains separate inventories for each quality grade. The results show that a grading system increases profit by an average of 4% over a wide range of parameter values commonly found in the remanufacturing industry; this number increases as the returns volume increases. We also numerically explore the case where there are capacity constraints and find the average improvement of a grading system remains around 4%.     

A multicriteria decision making model for reverse logistics using analytical hierarchy process

Product recovery activities such as recycling, refurbishing and direct reuse are becoming integral to manufacturing supply chains. This study presents a multicriteria decision making model for reverse logistics using analytical hierarchy process (AHP). The AHP model evaluates a hierarchy of criteria and subcriteria, including costs and business relations, for critical decisions regarding network design. Using sensitivity analysis with AHP, the work provides insights into the preference ordering among eight alternative network configurations. For instance, the choice of test sites is largely dependent on the potential for cost savings on testing procedures and transportation of scrap, and this decision is not sensitive to the importance of business relations. By contrast, the choice of collection sites is largely determined by the relative importance of business relations considerations vs. cost considerations. As well, the processing location decision favors a third-party reprocessor if there is little need to protect proprietary product knowledge and cost savings is very important. The model is demonstrated using three case studies of real-world applications.     

基于碳标签制度的两级供应链协调机制研究

以市场需求随机的视角建立Stackelberg博弈模型,研究基于碳标签制度的供应商和零售商组成的两级供应链协调策略。模型引入产品碳足迹e₁作为决策变量,分别研究了在收益共享与成本共担契约下集中决策和分散决策中决策变量最优解及最优利润的变化情况。研究结果表明,在考虑碳排因素时集中决策相比于分散决策具有明显的优势;在参数满足一定条件下零售商通过与供应商共担碳减排成本,可以实现利润的增长,初步验证模型的契约设计的有效性。     

越库转运问题的自适应遗传算法研究

探讨一种固定运输模式下的越库转运问题--采用运输量不可拆分的单次运送方式以最小费用通过选择固定的运输路径将货物经过越库转运到目的地,其货物将可能在越库中停留甚至无法运到目的地,这将会导致库存成本和惩罚成本.文中证明了此类越库转运问题是强NP难题,因此本文针对该问题的特殊结构,提出一种采用了邻域搜索技术的自适应遗传算法(...     

考虑延时效应的供应链动态合作广告策略研究

广告的延时效应是供应链广告过程中的普遍现象,对供应链合作广告策略的制定具有重要影响.文章研究当产品品牌信誉受广告延时效应影响时供应链的合作广告策略问题,建立了含有时间延迟的品牌信誉动态模型和考虑品牌信誉的产品销售量模型.运用极大值原理,得到了制造商和零售商在分散式决策和集中式决策下的最优广告投入、品牌信誉和利润,以及分散式决策下制造商的最优合作广告参与率.研究发现:在集中式决策下制造商和零售商的最优广告投入和产品销售量均高于分散式决策下的相应值;延迟时间存在一个阈值,当延迟时间低于该阈值时,集中式决策下的供应链利润较高,反之则分散式决策下的供应链利润较高.研究结果为供应链合作广告策略的制定及供应链决策机制的选择提供了一定的参考.最后,通过数值算例分析了广告延迟时间对供应链最优广告策略及决策机制的影响.