价格相依随机需求下的逆向拍卖采购与定价联合决策

研究价格相依随机需求下零售商的逆向拍卖采购与定价联合决策问题。假定零售商首先确定一个采购合同,然后供应商投标,通过逆向拍卖选取一个获胜的供应商,由该供应商确定采购量并传递给零售商,同时零售商做定价决策影响其需求,目标是寻求一个最优的采购与定价策略以最大化零售商的期望利润。对于一般的随机需求函数,引进期望销售弹性这一新的概念并利用其性质证明零售商的期望收益(不包括采购费用)是采购量的凹函数,从而得到其最优的采购与定价策略。特别地,对正态需求分布情形给出了零售商的采购量和利润函数的解析表达式并进行数值分析。     

考虑供应风险和生产成本不确定性的供应链动态决策研究

考虑到供应风险和生产成本的不确定性,本文研究了买方或卖方实施努力既可能改善供应可靠性,同时又可能降低生产成本的供应链最优决策问题。分别构建了制造商努力和供应商努力的两阶段动态决策模型。分析了提升供应可靠性和降低成本的概率对两种模型中的最优采购数量、最优努力程度和上下游期望收益以及供应链期望收益的影响。同时在两种模型的比较中发现,制造商的最优努力与供应商的最优努力之间的差异与收益分享系数有关。相同努力效果下,制造商努力时的最优采购数量总是不小于供应商努力时的最优采购数量。相比供应商努力,制造商努力更有利于增加其自身的期望收益。然而,供应商以及整个供应链的期望收益却可能在供应商努力时更高。     

竞争环境下基于期权博弈的R&D投资决策研究

论述了企业在竞争环境下的研发投资决策优化问题,利用实物期权的方法,采用二人博弈的模型分析了两家实力均衡的企业在进行研发投资决策时可能采取的策略,有同时投资策略、追随者策略和领先者策略等,并给出各种情况下的最优投资时机.最后结合实证进行了结论验证.     

信用评分模型的设计与决策分析

本文对商业银行信贷业务中的贷款者的信用问题,运用决策分析提出了信用评分的设计原理及临界分值的确定方法,给出了最优贷款策略的期望收益和风险的计算公式。最后,以一例说明之。     

基于库存价值改变和随机需求的经济订货批量模型

大多数库存研究的重点都集中在各种复杂的限制条件和模型的变换上.没有考虑到库存本身可能发生贬值或增值的情况,而实际中库存本身常常会发生价值变化.针对以往库存模型中没有考虑库存价值变化的问题,提出了在需求为随机连续分布、库存价值发生变化情况下的单周期经济订货批量模型,给出了最优订货策略.模型中以先进先出为假设条件,基于报童模型的思想,以订货量为决策变量、期望收益为目标函数,结合随机需求的分布情况得到最优订货量和最大期望收益,并给出了相应的数学证明.通过算例对模型进行说明,并对影响最优订货批量和最大期望收益的各个参数进行敏感性分析.     

基于绩效比和合同约束的多阶段在线租赁

签订合同租赁是获得设备临时使用权的一种重要方式。设备承租方往往在不知道设备未来需求的情况下就需要确定合同的预租天数,这是一个在线决策问题。基于绩效比分析和线性分数规划方法,依次研究了合同约束下的单阶段和多阶段在线租赁决策问题,分别得到了最优的在线预租策略及其绩效比。借助于数值算例,进一步分析了日收益、租赁费、交易费和损失费等因素对最优预租策略及其绩效比的影响。研究结果可以为设备承租方确定预租天数提供一定的决策依据,也可以在确定租赁费、损失费等方面为设备出租方提供一定的理论指导。     

供应链成员信息共享技术策略博弈分析

运用博弈论分析不确定条件下供应链成员的信息共享技术策略。首先建立基于需求不确定和供应不确定两种参数的"供应商+零售商"的期望收益模型,证实在不确定条件下的存在双方期望收益的最优解;建立三阶段博弈模型,探讨双方信息共享技术策略的博弈关系;分析四种的均衡状态:探讨初始需求不确定性、供应商的信息推测能力与零售商收益的不同关系对双方信息共享技术策略的影响,结论显示:当初始需求不确定性较大时,零售商以拒绝策略为先,进一步的策略取决于供应商的信息推测能力及其对零售商收益的影响,如果该能力较强,零售商将采取接受策略,反之则反。     

合作新产品开发资金及知识投入决策研究

针对现有对合作新产品开发投入的研究常常忽略投入资源的多样性,考虑同时投入知识和资金的情况下,合作参与者的最优投入决策问题． 通过构建 Stackelberg 博弈模型,分别讨论了只有资金投入和同时含有资金与知识投入时,领导者和跟随者的投入情况,并对比研究了两种情况下合作双方投入决策的异同． 研究表明: 不同资源投入时,合作形成条件亦不相同,即只有在领导者收益比例更大时,领导者才可能考虑资金和知识的同时投入; 通过改变资金投入量、知识投入量和研发努力程度,可调整知识溢出水平以促使合作开发成功．     

多评价指标的首达目标的收益决策模型

本文研究了在限定时刻之前首先满足多个评价指标的收益决策问题,构造了离散时间状态下的依分布最优的决策模型,分析了模型的目标函数的性质,得到求解目标值的方法,并详细讨论了模型的最优策略的性质和结构,从而将最优策略限制在平稳策略中寻找.     

基于二次消费的收益分享合同研究

本文研究了在单个电信运营商和单个经销商构成的分散式供应链中,商品具有二次消费的特征,当运营商采用收益分享策略,经销商采取降价促销策略时,占主导地位的一方如何制订供应链合同相关条款,实现其期望利润最大化.本文建立了相应的模型并给出了最优解,并通过算例加以说明.     

A bilevel programming problem with maximization of a supermodular function in the lower level

In bilevel programming there are two decision makers, the leader and the follower, who act in a hierarchy. In this paper we deal with a bilevel problem where the follower maximizes a supermodular function. The payoff for the leader is given by the weighted set that is chosen by the follower. To increase his payoff the leader can increase the supermodular function of the follower by a modular one, thus influencing the follower’s decision, but he has to pay a penalty for this. We want to find an optimum strategy for the leader. This is a bilevel programming problem with continuous variables in the upper level and a parametric supermodular maximization problem in the lower level. We analyze the structure of the bilevel problem. This we use to provide an equivalent one-level combinatorial problem. Finally, we investigate the properties of the new problem.     

Optimality conditions for a bilevel matroid problem

In bilevel programming there are two decision makers, the leader and the follower, who act in a hierarchy. In this paper we deal with a weighted matroid problem where each of the decision makers has a different set of weights. The independent set of the matroid that is chosen by the follower determines the payoff to both the leader and the follower according to their different weights. The leader can increase his payoff by changing the weights of the follower, thus influencing the follower’s decision, but he has to pay a penalty for this. We want to find an optimum strategy for the leader. This is a bilevel programming problem with continuous variables in the upper level and a parametric weighted matroid problem in the lower level. We analyze the structure of the lower level problem. We use this structure to develop local optimality criteria for the bilevel problem that can be verified in polynomial time.     

A market regulation bilevel problem: A case study of the Mexican petrochemical industry

In this paper, a bilevel programming model is proposed to study a problem of market regulation through government intervention. One of the main characteristics of the problem herein analyzed is that the government monopolizes the raw material in one industry, and competes in another industry with private firms for the production of commodities. Under this scheme, the government controls a state-owned firm to balance the market; that is, to minimize the difference between the produced and demanded commodities. On the other hand, a regulatory organization that coordinates private firms aims to maximize the total profit by deciding the amount of raw material bought from the a state-owned firm. Two equivalent single-level reformulations are proposed to solve the problem. The first reformulation is based on the strong duality condition of the lower level and results in a continuous non-linear model. The second reformulation resorts to the complementarity slackness optimality constraints yielding a mixed-integer linear model. Additionally, three heuristic algorithms are designed to obtain good-quality solutions with low computational effort. In this problem, the feasible region of the dual problem associated to the follower is independent from the leader’s decision. Therefore, the proposed heuristics exploit this particular characteristic of the bilevel model. Moreover, the third heuristic hybridizes the other two algorithms to enhance its performance. Extensive computational experimentation is carried out to measure the efficiency of the proposed solution methodologies. A case study based on the Mexican petrochemical industry is presented. Additional instances generated from the case study are considered to validate the robustness of the proposed heuristic algorithms. Numerical results indicate that the hybrid algorithm outperforms the other two heuristics. However, all of them demonstrate to be good alternatives for solving the problem. Additionally, optimal solutions of all the instances are obtained by using good quality solutions (given by the hybrid algorithm) as initial solutions when solving the second reformulation via a general purpose solver.     

一类供应链的Stackelberg主从对策问题研究

本文研究了供应链中的一般订货模式和协调模式,提出了一类供应链Stackelberg主从对策问题,卖方作为主方给出最小补充期策略,买方作为从方以最优库存策略响应。考虑一致价格折扣弥补买方的库存成本增加,以及买方的库存成本合理化,建立买方需求确定下的卖方成本优化模型。最后,应用遗传算法对石油分销系统Stackelberg主从对策问题离线仿真计算,得出Stackelberg主从对策均衡解。     

两级供应链Stackelberg主从对策的优化模型及其应用

本文研究了供应链的协调订货模式及其特例,提出了两级供应链Stackelberg主从对策问题模型,其中卖方作为主方给出最小补充期策略,买方作为从方以最优库存策略响应。建立了求解Stackelberg主从对策问题的成本优化模型,并考虑了累积价格折扣激励和买方库存成本合理化。对一个石油分销系统Stackelberg主从对策问题应用遗传算法离线仿真计算,得出Stackelberg均衡解,达到帕累托最优。     

Transformational leadership and follower creativity: The mediating role of follower relational identification and the moderating role of leader creativity expectations

We examined follower relational identification with the leader as a mediator and follower perceptions of leader creativity expectations as a moderator in the relationship between transformational leadership and follower creativity. Using a sample of 420 leader–follower dyads from an energy company in mainland China, we found that follower relational identification with the leader mediates the transformational leadership–follower creativity relationship, and this mediating relationship is conditional on the moderator variable of follower perceptions of leader creativity expectations for the path from follower relational identification to follower creativity. These results contribute to the literature by clarifying why (through relational identification) and when (high creativity expectations set by the leader) transformational leadership is positively related to follower creativity.     

Planning of a decentralized distribution network using bilevel optimization

This paper proposes a bilevel optimization problem to model the planning of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. Usually, the distribution network design problem decides on the opening of depots and the distribution from the depots to customers only and pays no attention to the manufacturing process itself. By way of example, the paper discusses the implications of formulating a bilevel model to integrate distribution and manufacturing, maintaining the hierarchy existing in the decision process. The resulting model is a bilevel mixed integer optimization problem. Hence, only small instances can be optimally solved in an acceptable computing time. In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.     

求解非线性二层规划问题的模拟植物生长算法

本文以植物向光性生长理论为启发式准则,提出了一种求解非线性二层规划问题的智能优化算法。在该算法中,将二层规划上层解空间和下层反应集分别作为植物的两个生长环境,建立以生长规则为基础的植物系统演绎方式和以植物向光性理论为基础的概率生长模型,两者结合所形成的优化模式,实现了模拟植物从初始状态到完整形式的终态(没有新的树枝生长),从而得到二层规划问题的解。该方法具有搜索精度较高,求解稳定性较强的特点,通过与国外学者在非线性二层规划实际测试问题的最优值进行精度比较,表明模拟植物生长算法是有效可行的。     

基于混合智能算法的电子市场供应链期权合同协调

在电子市场环境下,考虑了需求、市场价格和市场准入程度的随机性,基于Stack-erlberg主从对策,建立了供应链期权合同协调的随机期望值模型。在这一主从对策模型中,主方供应商的目标函数是预期利润,决策变量是期权合同预订费用和执行费用;从方分销商的目标函数是预期利润,决策变量是订货量。应用包括随机模拟、人工神经元网络和遗传算法组成的混合智能算法求解该主从对策问题。最后,结合上海宝钢集团益昌公司电子商务的运作实例,运用混合智能算法进行了仿真计算与分析。     

Balance in leader and follower perceptions of leader–member exchange: Relationships with performance and work attitudes

Using a sample of 285 matched pairs of employees and supervisors, we explore the extent to which congruence in leader and follower ratings of LMX quality is related to follower job performance and work attitudes. An original conceptual model is introduced that identifies four combinations of leader and follower LMX ratings: balanced/low LMX (low leader and follower LMX), balanced/high LMX (high leader and follower LMX), follower overestimation (low leader LMX/high follower LMX), and follower underestimation (high leader LMX/low follower LMX). As expected, balanced/low (high) LMX relationships were associated with relatively low (high) levels of follower job performance, organizational commitment, and job satisfaction, while the incongruent combinations generally yielded intermediate levels of follower outcomes. However, follower underestimation was also related to high levels of follower job performance, whereas follower overestimation was associated with high levels of follower satisfaction and organizational commitment. Implications of these findings for future LMX research are considered.