Pricing and capacity allocation strategies: Implications for manufacturers with product sharing

Emerging sharing modes, like the consumer-to-consumer (C2C) sharing of Uber and the business-to-consumer (B2C) sharing of GoFun, have considerably affected the retailing markets of traditional manufacturers, who are motivated to consider product sharing when making pricing and capacity decisions, particularly electric car manufacturers with limited capacity. In this paper, we examine the equilibrium pricing for a capacity-constrained manufacturer under various sharing modes and further analyze the impact of capacity constraint on the manufacturer's sharing mode selection as well as equilibrium outcomes. We find that manufacturers with low-cost products prefer B2C sharing while those with high-cost products prefer C2C sharing except when the sharing price is moderate. However, limited capacity motivates manufacturers to enter into the B2C sharing under a relatively low sharing price, and raise the total usage level by sharing high-cost products. We also show that the equilibrium capacity allocated to the sharing market with low-cost products first increases and then decreases. Finally, we find that sharing low-cost products with a high limited capacity leads to a lower retail price under B2C sharing, which creates a win-win situation for both the manufacturer and consumers. However, sharing high-cost products with a low limited capacity creates a win-lose situation for them.     

Callable products with dependent demands

Capacity providers such as airlines often sell the same capacity to different market segments at different prices to improve their expected revenues. The absence of a secondary market, due to the nontransferability of airline tickets, gives rise to an opportunity for airlines to broker capacity between consumers with different willingness to pay. One way to broker capacity is by the introduction of callable products. The idea is similar to callable bonds where the issuer has the right, but not the obligation, to buy back the bonds at a certain price by a certain date. The idea of callable products was introduced before under the assumption that the fare-class demands are all independent. The independent assumption becomes untenable when there is significant demand recovery (respectively, demand cannibalization) when lower fares are closed (respectively, opened). In this case, consumer choice behavior should be modeled explicitly to make meaningful decisions. In this paper, we consider a general consumer choice model and develop the optimal strategy for callable products. Our numerical study illustrates how callable products are win-win-win, for the capacity provider and for both high and low fare consumers. Our studies also identify conditions for callable products to result in significant improvements in expected revenues.     

鱼雷耦合非线性系统的线性控制方法

给出了鱼雷空间运动的数学模型;在流形上研究了非线性系统的线性化系统可控时的镇定问题,给出了线性控制规律使非线性控制系统镇定于原平衡点的条件;基于线性化拓扑等价性定理,将鱼雷三通道的非线性模型进行等价变换,利用传统的线性设计方法和多变量控制方法分别去处理鱼雷耦合非线性系统的控制问题,从而降低了多通道耦合控制设计问题的难度和复杂性。     

软件可靠性分配的遗传模型研究

对软件可靠性分配的遗传模型进行了研究,结合相关知识缩小了基本遗传算法的搜索区域,比较灵活地处理了非线性约束条件,提高了搜索效率,避免了早熟收敛现象.此外,在基本遗传算法中增加了保优操作,从而能够在理论上保证实现分配的最优化.算例表明,该算法十分有效.     

加强建筑消防设计审核工作之思考

结合自己的工作实践 ,分析建筑消防设计审核工作的重要性 ,并对如何加强建筑消防设计审核工作提出了看法。     

测试性增长中资源优化配置模型及求解

良好的测试性设计对系统维修性具有重要意义,测试性增长试验通过一系列测试性设计缺陷发现和纠正措施,可保证系统测试性指标达到设计要求。针对基于延缓纠正的测试性增长过程中的资源配置问题进行研究,基于增长试验目标是否明确和试验资源是否受限制问题构建资源优化配置模型,并提出一种基于拉格朗日松弛和本地搜索的快速优化算法。仿真结果表明:该模型能够有效指导测试性增长中的资源优化配置问题,所提混合优化方法能够高效、准确地求解整数规划问题。     

二维非线性正交异性材料的瞬态热传导反问题研究

针对正交异性材料的二维非线性热传导反问题,本文采用顺序函数法对表面热流辨识进行了研究。在求解反问题时用到有限体积法、牛顿-拉夫逊法并引入未来时间步长的概念。在每个时间步内,将待辨识热流视为非线性方程组的未知量,通过一个迭代过程进行求解。从文中的例子可以看出,真实热流和辨识热流结果相近,从而证明了本方法在辨识二维非线性热传导反问题时是准确、稳定、有效的。     

A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times

We investigate a single‐machine scheduling problem for which both the job processing times and due windows are decision variables to be determined by the decision maker. The job processing times are controllable as a linear or convex function of the amount of a common continuously divisible resource allocated to the jobs, where the resource allocated to the jobs can be used in discrete or continuous quantities. We use the common flow allowances due window assignment method to assign due windows to the jobs. We consider two performance criteria: (i) the total weighted number of early and tardy jobs plus the weighted due window assignment cost, and (ii) the resource consumption cost. For each resource consumption function, the objective is to minimize the first criterion, while keeping the value of the second criterion no greater than a given limit. We analyze the computational complexity, devise pseudo‐polynomial dynamic programming solution algorithms, and provide fully polynomial‐time approximation schemes and an enhanced volume algorithm to find high‐quality solutions quickly for the considered problems. We conduct extensive numerical studies to assess the performance of the algorithms. The computational results show that the proposed algorithms are very efficient in finding optimal or near‐optimal solutions. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 41–63, 2017     

军事云环境下基于动态博弈的资源调度方法

针对军事云环境下联合指挥资源调度优化问题,综合考虑了多部队任务需求,多目标优化,多部队资源竞争等约束条件,运用动态博弈理论及方法,建立并提出了一种基于完全信息扩展博弈的资源调度模型及方法,提高了资源调度效率,兼顾了多部队利益,增加了联合作战效益。最后通过实验验证了其有效性及准确性。     

子弹均匀散布子母弹最有利火力分配方法

在将子弹均匀散布的椭圆区域等效转换为矩形区域的基础上,建立了适宽射向射击子母弹对矩形目标毁伤全概率计算的数学模型。通过函数转换和泛函分析给出了子弹均匀散布子母弹理想射击密度,得到了理想射击密度下对目标的毁伤概率计算公式。讨论了最有利火力分配方式的确定方法,给出了最优射向间隔和表尺差的计算公式,为便于实际应用,给出了最优火力分配计算中所需的3个参数的近似计算公式,最后给出了应用算例。