考虑政府补贴的新产品与再制造产品定价模型

在有限财政预算下,政府对再制造产品进行补贴,以促进再制造产品的生产和销售.基于此,首先建立政府对制造商进行生产补贴的三层决策模型,该模型中制造商与新产品销售商和再制造产品销售商进行Stackelberg博弈,同时两个销售商之间通过Bertrand博弈确定各自的销售价,通过对解的分析,揭示生产补贴对批发价、销售价以及销售量的影响,并通过与无补贴销售量的比较,进一步给出政府补贴提升再制造产品销量的根本原因;然后给出对再制造产品销售商进行销售补贴下的三层模型,证明销售补贴与生产补贴在影响销售价格、销售量方面的等价性;接着讨论集中决策供应链中新产品与再制造产品销售的二层决策模型,比较集中决策供应链与分散决策供应链再制造产品的销售量高低并分析其原因,指出政府倾向于优先补贴的供应链类型;最后给出一个算例,分析不同类型供应链中再制造产品销售量对参数的敏感性.     

Revisiting revenue management for remanufactured products

The purpose of revenue management for remanufactured products is to maximise the expected revenue for remanufactured products. Most researchers in revenue management focus on analysing the sensitivity of the expected revenue to price, availability and disposal cost. In this note, we apply the Karush–Kuhn–Tucker conditions with maximum price constraints, and demonstrate that the optimal prices for the non-linear problem fall within the feasible region when constraints are imposed. A numerical example is given to illustrate the proposed study.     

Determining the prices of remanufactured products,capacity of internal workstations and the contracting strategy within queuing framework

This paper studies a remanufacturing facility with several types of incoming nonconforming products and different independent remanufacturing workstations. The workstations have limited capacities so that an outsourcing strategy can be practiced. Each workstation is modeled with an M/M/1/k queuing system considering k as a decision variable. Additionally, a binary decision variable is taken into account to determine the contracting strategy along with some decision variables for the prices of remanufactured products. Thus, a bi-objective mixed-integer nonlinear programming is built to obtain optimal values of the decision variables. The first objective attempts to maximize the total profit and the second minimizes the average length of queuing at workstations. To solve the complex bi-objective mixed-integer nonlinear programming problem, the best out of six multi-objective decision-making (MODM) methods is selected in order to make the bi-objective optimization problem a single-objective one. Afterward, a genetic algorithm (GA) is developed to find a near-optimum solution of the single-objective problem. Besides, all of the important parameters of the algorithm are calibrated using regression analysis. To validate the results obtained, the solutions of some test problems are compared to the ones obtained by the GAMS software. The applicability of the proposed model and the solution procedure are shown with an illustrative example.     

基于WCVaR的易逝品生产分销网络优化策略

针对需求信息概率分布部分已知下的易逝品生产-分销网络,引入最坏条件风险值(WCVaR)对易逝品的生产-分销网络进行风险度量。在考虑产品生产、物流量分配、运输路径选择等因素对生产成本、运输成本、存储成本以及缺货损失影响的基础上,建立满足一定服务水平下最坏情景网络风险值最小的优化模型,并通过最小化生产-分销网络的尾部风险损失实现易逝品生产-分销网络最佳优化策略。模型数值仿真结果表明:相比稳健优化,WCVaR方法不仅能处理更具波动的不确定,而且具有更优的稳定性;当需求变量为混合分布时,WCVaR优化模型可较好解决生产-分销网络不确定优化问题。     

线上渠道模式与制造商分销策略的匹配关系

在转销和代销这两种典型的线上渠道模式下,构建制造商、实体店和电商之间的博弈模型,探讨线上渠道模式与制造商分销策略之间的匹配关系.研究结果表明:当消费者对产品差异的敏感程度较小(较大)时,制造商的分销策略选择与线上渠道模式无关,其会选择线下销售低端(高端)产品,线上销售高端(低端)产品的分销策略;当消费者对产品差异的敏感程度适中时,若线上为转销模式,则制造商应该选择线下销售高端产品,线上销售低端产品的分销策略;若线上为代销模式,则制造商应该选择线下销售低端产品,线上销售高端产品的分销策略.在不同的分销策略情形下,增大线上线下销售产品的差异化程度有利于提高制造商的利润水平.研究结果为线上线下渠道实现融合发展提供了理论指导.     

Optimal versioning strategy for information products with behavior-based utility function of heterogeneous customers

This paper reconsiders two fundamental assumptions (i.e., on the quality of information product and the self-selection behavior of customers) that decide the optimality of versioning strategy (or vertically differentiated product line) for information products. The quality of an information product is clarified in terms of functional and nonfunctional features. The customers? behavior of self-selection among multiple versions of an information product is examined, and the disability of linear valuation function for exactly capturing customers? valuation on information products is clarified. The required quality is introduced to depict a customer?s requirement on the quality of an information product, and a behavior-based utility function is thus defined, where a customer has a marginal decrease (different from the constant marginal in linear valuation function) on the valuation of versions with quality levels higher than the required, but the valuation of a customer diminishes quickly on versions with quality levels lower than the required. Then, a bilevel programming model is built to represent the task for optimizing the strategy of versioning an information product, with the monopolist as the leader and all customers as followers. Optimal quality levels and prices for multiple versions are obtained for a given number of versions. To deal with the nonlinearity and multimodality of this model due to correlated decision variables, a steady-state evolutionary algorithm, hybridized with the local search method (called the hybrid steady-state evolutionary algorithms), is developed to improve the global optimality of versioning schemes. Numerical experiments are conducted on the bilevel programming model with specific parameterization by using the hybrid algorithm. Experimental results verify the optimality of multi-version strategy and reveal various facets of its property. With the behavior-based valuation function of heterogeneous customers, the multi-version strategy is superior to the one-version scheme. The total profit increases logarithmically with the maximal number of versions, which means that the introduction of a new lower-quality version contributes less to the total profit of a monopolist. Furthermore, when a lower quality level version is offered to the market, higher quality versions are priced higher than they were in previous versioning schemes, indicating that a multi-version scheme can make more detailed segmentation of the market. Therefore, a monopolist is able to gain greater revenue via price discrimination on heterogeneous customers through vertically differentiating information products.     

Design process and data models to support the design of sustainable remanufactured products

The need for increased levels of reuse and remanufacturing is driving the need for sustainable design of remanufactured products. It is acknowledged that design for remanufacturing benefits the environment. However, it seldom integrates eco-design approaches as it requires ‘life cycle thinking’ with closed-loop life cycles. The objective of this paper is to support eco-design of remanufactured products with design process and data models structuring the activities to be performed and providing the support required. We consider the development of two activities in particular: definition of the target, and environmental analysis. The first activity exploits the concept of RPP (Remanufacturable Product Profile), building on the criteria that are crucial for a successful remanufactured product. The second one exploits the life cycle brick concept that associates each product component with a specific life cycle and related environmental impacts. The models proposed are exploited in a case study concerning the design of remanufactured truck gearboxes.     

Optimal signal design strategy with improper Gaussian signaling in the Z-interference channel

We propose a thoroughly optimal signal design strategy to achieve the Pareto boundary (boundary of the achievable rate region) with improper Gaussian signaling (IGS) on the Z-interference channel (Z-IC) under the assumption that the interference is treated as additive Gaussian noise. Specifically, we show that the Pareto boundary has two different schemes determined by the two paths manifesting the characteristic of improperly transmitted signals. In each scheme, we derive several concise closed-form expressions to calculate each user’s optimally transmitted power, covariance, and pseudo-covariance of improperly transmitted signals. The effectiveness of the proposed optimal signal design strategy is supported by simulations, and the results clearly show the superiority of IGS. The proposed optimal signal design strategy also provides a simple way to achieve the required rate region, with which we also derive a closed-form solution to quickly find the circularity coefficient that maximizes the sum rate. Finally, we provide an in-depth discussion of the structure of the Pareto boundary, characterized by the channel coefficient, the degree of impropriety measured by the covariance, and the pseudo-covariance of signals transmitted by two users.     

零售商多种价格策略下的最优订购模型

同种产品以多种价格同时销售(多种价格策略)是零售商常用的折扣策略,为了找到多种价格策略下零售商实现期望利润最大化的订购量,对经典报童模型进行拓展,分别从无订购量约束和订购量约束两方面进行研究和讨论.在多种价格对应消费者需求不确定情况下建立一个新的报童模型,使用拉格朗日乘子法求解订购量约束问题,并设计近似最优总订购量的求解算法.数值分析结果表明:多种价格策略优于单一价格策略,订购量约束对零售商多种价格策略的选择会产生影响;在有订购量约束情况下,零售商的多种价格策略还会受到价格折扣系数、需求差异性的影响.     

A new load distribution strategy for linear network with communication delays

In this paper, we propose a new load distribution strategy called ‘send-and-receive’ for scheduling divisible loads, in a linear network of processors with communication delay. This strategy is designed to optimally utilize the network resources and thereby minimizes the processing time of entire processing load. A closed-form expression for optimal size of load fractions and processing time are derived when the processing load originates at processor located in boundary and interior of the network. A condition on processor and link speed is also derived to ensure that the processors are continuously engaged in load distributions. This paper also presents a parallel implementation of ‘digital watermarking problem’ on a personal computer-based Pentium Linear Network (PLN) topology. Experiments are carried out to study the performance of the proposed strategy and results are compared with other strategies found in literature.     

BOPS渠道下制造商优惠券投放决策和零售商增值服务策略演化研究

为了合力开通BOPS渠道,制造商进行优惠券促销,零售商决定是否提供增值服务,构建单次Bertrand- Stackelberg博弈模型和单种群零售商对称性演化博弈模型,以此分析一般均衡结果和零售商群体的演化稳定策略.可以发现:不同策略组合下的双寡头零售商具备“囚徒困境”的博弈特征,制造商能够以批发定价和优惠券面值双重调控零售商的定价行为和服务策略选择;提供增值服务是零售商群体存在的唯一演化稳定策略,参数的变动影响演化稳定区域的大小;在引入价格偏好特征的拓展模型中,零售商群体只会达成混合策略演化均衡,且群体中选择提供增值服务策略的零售商数量始终只占较小比例.     

A new joint strategy of radio channel allocation and power control for wireless mesh networks

For wireless mesh networks, it is critical to allocate the limited number of radio channels efficiently while mitigating the co-channel inference to improve network performance. For this reason, after extensively reviewing the related work, we present a new joint radio channel allocation (RCA) and power control (PC) strategy for wireless mesh networks. First, we formulate the RCA problem as a multiple objective optimization problem, with the constraints of transmission power and traffic data rates, while effective channel utilization (ECU) is chosen as the target metric for optimization. Second, we incorporate the channel status into the model of MAC protocols, including as signal-to-noise ratio (SNR) and transmission power. Consequently, the PC is incorporated into the ECU for channel allocation. Third, we propose to directly maximize the ECU to find both optimal radio channel and transmission power. The resulting strategy is a fully distributed RCA/PC algorithm without relying on a coordination mechanism among mesh routers. Our extensive simulation results have demonstrated that the proposed algorithm significantly outperforms the existing RCA strategies and the standard MAC protocols in performance such as throughput, packet dropping, delay and delay jitter.     

Optimal pricing model for electronic products

Electronic commerce encompasses all electronically conducted business activities, operations, and transaction processing. With the development of electronic commerce via Internet, during the past decade, many companies have changed the way they connect to and deal with their customers and partners. In this paper we introduce a Geometric Programming (GP) based model to analyze the pricing method and the service quality for E-business companies. The proposed method of this paper considers electronic products which are all kinds of products to be sold via web supermarkets. Therefore, they can cover pure digital and also non-digital products. The model proposed in this research work, deals with non-digital goods, which are supplied through web. The resulted non-linear model is directly solved by using Geometric Programming (GP) and a closed form of solution is presented. We assume that the demand is influenced by price, marketing and service expenditures. We also assume that the cost of production is affected by demand. We analyze the solution in different cases, in order to study the behavior of the model and for each case numerical examples are used to demonstrate the implementation of our analysis. The sensitivity analysis is also presented at the end to analyze the behavior of the model.     

Optimal incentive strategy for leader-follower games

An optimal incentive strategy by which the leader suffers the least losses in punishing the follower's deviation from the decision desired by the leader is defined. Sufficient conditions for the existence of optimal incentive strategy are given. Static and dynamic leader-follower games with quadratic cost functionals are investigated. It is shown that leader-follower games with quadratic cost functionals admit optimal incentive strategies under the follower's decision variable being scalar, there exists a unique linear optimal incentive strategy. Such an incentive strategy can be explicitly determined     

Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS

Distribution channel management not only consists of choosing distribution channels. In fact, probably the most difficult phase of the distribution management starts after this choice. Determining an appropriate organization strategy for distribution channel management is like a problem of concern to marketing practitioners and academics as well in this phase. In this study, the organization strategy of distribution channel management is developed using fuzzy analytic hierarchy process (FAHP) and hierarchical fuzzy TOPSIS (HFTOPSIS) for an edible-vegetable oils manufacturer firm operating in Turkey. The company distributes its products all over the country. Due to the complex structure of the distribution network, the company wants to decide the organization strategy to manage the distribution channels. In this paper, the methods of FAHP and HFTOPSIS for evaluating and selecting among the five organization strategy models for distribution channel management of vegetable oil manufacturer have been presented. The proposed models include determinants of distribution channel management for edible-vegetable oil industry; (i) customer profile, (ii) distributor reliability, (iii) the position of competitors in market, and (iv) managerial and financial perspective. Using FAHP and HFTOPSIS, hybrid based strategy (KBS), which has the greatest desirability index value after the evaluation among the five alternatives is found as the best choice. Thus, the case of the vegetable oil manufacturer company provides the researchers and practitioners to understand in a better way the importance of developing organization strategy in channel management from a practical point of view.     

Optimal transshipment of products

Cost optimization based on mathematical programming is described for a fixed-time-interval transshipment problem with capacity constraints on paths between warehouses and rotail outlets. Stochastic optimization is achieved by coupling deterministic linear programming with Monte Carlo simulation, and this procedure is further extended to include serial and cross correlations. In addition, posterior information may be considered by invoking the Bayes theorem. Non-linear systems are also treated.     

Optimal location selection for an international distribution center by using a new hybrid method

The selection of a location for an international distribution center (IDC) is a most important decision for international logistics managers owing to the need to consider various criteria that involve a complex decision process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. Moreover, the criteria often exist simultaneously as independent and dependent characteristics when the problems of location selection have become very complex. A new hybrid method combining the concepts of fuzzy DEMATEL and a new method of fuzzy multiple criteria decision-making (MCDM) in a fuzzy environment is proposed to solve the problems of IDC location selection. In this paper, the fuzzy DEMATEL is proposed to arrange a suitable structure between criteria, and the analytic hierarchy/network process (AHP/ANP) is used to construct weights of all criteria. The linguistic terms characterized by triangular fuzzy numbers are used to denote the evaluation values of all alternatives versus various criteria. Finally, the aggregation fuzzy assessments of different alternatives are ranked to determine the best selection. Furthermore, this paper uses an empirical case for optimal location selection for an IDC in Pacific Asia to illustrate the proposed method, and the results show that the method is an effective means for tackling fuzzy MCDM problems.     

季节性产品零售商的网络订单履行策略研究

以一个销售季节性产品的零售商为研究对象,该零售商拥有两个实体店,分别位于两个独立的地区,通过Drop-shipping方式接收网上的订单,以扩大销量。初始库存量是确定的,产品卖给网上顾客为零售商带来的收益要比卖给店内顾客的收益少（履行网上订单获得的收益是零售商与订单提供者共享）;因此,每当网上订单到达时,零售商需要在接收该订单、还是把产品留给能带来更高收益的未来的店内顾客间做决策;如果接收该订单,还要决策将由哪个实体店来履行订单效益更好;以最大化未来期望收益为目标,建立动态规划模型,并从实体店对单个产品期望收益的角度为这两个问题的决策提供依据;分别在两个实体店处于平等地位和其中一个实体店被确定为优先供应商两种不同的情况下,研究零售商决策结果的差异。     

基于新量子遗传算法的无线传感器网络感知节点的分布优化

无线传感器网络中,感知节点的合理分布对于提高网络的感知能力和收集信息能力都具有重要作用。对于随机分布方式产生的感知网络,可以利用节点的移动性对特定感知节点的位置进行调整从而改善网络整体的感知覆盖范围。为此,针对无线传感器网络感知节点的分布优化问题进行了研究,给出了无线传感器网络覆盖控制模型,并提出了一种基于新量子遗传算法的分布优化机制。仿真结果表明新量子遗传算法在优化性能上优于传统遗传算法,能够有效提高网络整体的感知能力。