代理人努力决策柔性的分成制委托代理模型

针对被忽视的代理人努力决策的柔性,在第0期完全信息条件下建立了基于柔性的代理人努力决策模型和委托人的最优分成制合同设计模型,证明了最优分成比例在柔性决策行为假定下的存在性,并与经典的委托-代理模型的结论进行对比分析.结果表明,努力决策柔性将会提高努力所要求的临界市场价格;最优分成比例随着代理人的努力成本增加而增加,随着市场价格的期望增长率和努力的产量的增加而减小,但不会随着市场价格的波动率的增加而降低;当市场状况差时,经典的委托代理理论给出的分成比例将会给予代理人过高的支付.     

The Center Location Improvement Problem Under the Hamming Distance

In this paper, we consider the center location improvement problems under the sum-type and bottleneck-type Hamming distance. For the sum-type problem, we show that achieving an algorithm with a worst-case ratio of O(log |V|) is NP-hard, and for the bottleneck-type problem, we present a strongly polynomial algorithm.     

An upper bound on the minimal total cost of the transportation problem with varying demands and supplies

In general cases, to find the exact upper bound on the minimal total cost of the transportation problem with varying demands and supplies is an NP-hard problem. In literature, there are only two approaches with several shortcomings to solve the problem. In this paper, the problem is formulated as a bi-level programming model, and proven to be solvable in a polynomial time if the sum of the lower bounds for all the supplies is no less than the sum of the upper bounds for all the demands; and a heuristic algorithm named TPVDS-A based on genetic algorithm is developed as an efficient and robust solution method of the model. Computational experiments on benchmark and new randomly generated instances show that the TPVDS-A algorithm outperforms the two existing approaches.     

A shelf-space optimization model when demand is stochastic and space-elastic

The more customer demand is impulse-driven, the more it is space-dependent and the more it is subject to variation. We investigate the corresponding problem of retail shelf-space planning when demand is stochastic and sensitive to the number and position of facings. We develop a model to maximize a retailer׳s profit by selecting the number of facings and their shelf position under the assumption of limited space. The model is particularly applicable to promotional or temporary products.We develop the first optimization model and solution approach that takes stochastic demand into account, since the current literature applies deterministic models for shelf-space planning. By the means of an innovative modeling approach for the case with space- and positioning effects and the conversion of our problem into a mixed-integer problem, we obtain optimal results within very short run times for large-scale instances relevant in practice. Furthermore, we develop a solution approach to account for cross-space elasticity, and solve it using an own heuristic, which efficiently yields near-optimal results. We demonstrate that correctly considering space elasticity and demand variation is essential. The corresponding impacts on profits and solution structures become even more significant when space elasticity and stochastic demand interact, resulting in up to 5% higher profits and up to 80% differences in solution structures, if both effects are correctly accounted for. We develop an efficient modeling approach, compare the model results with approaches applied in practice and derive rules-of-thumb for planners.     

带有快速反应策略供应链系统的补偿策略研究

过长的订购提前期往往使得零售商订货决策感到困难. 快速反应策略能使零售商在获 得更多更准确的市场需求信息后,调整订购量而提高收益. 但是快速反应策略并不一定使供应 商的利润也提高. 有文章指出只有低的服务水平才能使两者利润同时提高,因而这种方法在工 业应用中是不一定可行的. 补偿策略是一种广泛应用的方法,能够提高产品的客户服务水平, 因而研究了补偿策略在快速反应供应链系统中的作用. 在某些条件下,在快速反应供应链系统 中,补偿策略能使零售商与供应商一方的收益不变或者提高,另一方的收益有所提高,即Pare2 to 提高. 还研究了引进补偿策略后,供应链系统的最优解及期望卖出量、期望缺货量和期望残 余量的变化情况.     

On Approximability of Boolean Formula Minimization

For a Boolean function given by a Boolean formula (or a binary circuit) S we discuss the problem of building a Boolean formula (binary circuit) of minimal size, which computes the function g equivalent to , or -equivalent to , i.e., . In this paper we prove that if P NP then this problem can not be approximated with a good approximation ratio by a polynomial time algorithm.     

运力受扰的多车场车辆调度干扰管理问题研究

为解决物流配送系统中因运输车辆毁坏而产生的干扰问题,基于干扰管理思想提出了解决问题的扰动恢复策略与实施方案。在扰动度量的基础上,设计了多车场车辆调度扰动恢复策略,建立相应的干扰管理模型。针对多车场车辆调度干扰管理问题的特有属性,设计了一系列求解简化策略,有效简化了问题的求解空间。结合干扰管理模型的特点,使用改进的遗传算法进行求解。最后给出了一个算例,其结果证明了干扰管理模型与算法的有效性。     

基于演化博弈的供应链协同产品开发合作机制研究

针对由制造商与供应商构成的两层供应链系统,基于演化博弈理论和方法,研究在长期的协同产品开发过程中,有限理性的制造商和供应商之间的合作机制。首先,对合作的成本分担与收益分配机制进行了分析;然后,对监督和惩罚机制进行了探讨。理论研究、数值模拟和实例分析结果表明:双方进行协同产品开发合作的概率与合作超额收益和单独研发的收益正相关、与研发总费用和背叛收益负相关;存在一个最优的超额收益分配比例,使得制造商和供应商合作的可能性最大化;合作双方支付的成本与双方合作超额收益的分配正相关;在监督条件下,合理的惩罚将有利于减少背叛行为。     

A multiple-item budget-constraint newsboy problem with a reservation policy

In contrast to the classical newsboy-style problem, this paper develops a model for the multiple-item budget-constraint newsboy problem considering a reservation policy to meet marketing needs. A discount rate is provided to those customers who are willing to make a reservation. In addition to the demand from the original customers, extra demand is also included in the model due to the motivation of the discount rate. A solution algorithm, namely the MCR algorithm, is proposed to solve the problem. The proposed algorithm can actually be considered as a generalization of the classical newsboy-style problem. The MCR algorithm not only provides a business unit with the optimal order quantity, but also the discount rate necessary to achieve the maximal total expected profit under a limited budget. From the illustrated example, it is shown that the expected profit from the proposed model is greater than that from the classical model, due to the consideration of reservations, even though the budget constraint is tight. The increase in the expected profit could be treated as an information value from the willingness function. Although the proposed model is developed for multiple-item problems, it also can be applied to single-item ones. From the sensitivity analysis, the application of the single-item problem to the proposed model can still obtain greater expected profit than the classical model under different budgetary levels.     

考虑风险规避的秘书问题求解的一个启发式方法

秘书问题是一类序贯观察与选择问题,描述了动态的信息搜索与决策过程.针对现有的以寻找满意解为目标的启发式方法存在诸多局限,提出了新的启发式方法,该方法基于当前观测中侯选项在已观察侯选项中的相对排名、待观测侯选项数量以及决策者的抱负水平,决策者可以通过设定抱负水平灵活决定该启发式方法的结果导向.推导了该启发式方法的性能指标,并通过仿真的方法与已有启发式方法的性能进行了比较.结果发现,该启发式方法在最终选择的侯选项的期望排名和稳定性,以及风险解的避免上均优于已有的启发式方法.