基于泊松跳跃的最佳并购时机比较研究

基于最优停时理论、实物期权方法、平滑粘贴条件和道格拉斯生产函数转换,通过时机模型构建与求解,比较分析了无泊松跳跃和有泊松跳跃两种情形下的最佳并购时机。研究结果显示,驱动企业并购的主要是协同效应;企业并购存在仅与并购双方相对股价有关的最佳并购时机及其对应的并购区域;泊松跳跃使并购阈值下界和并购阈值上界右移,并购区域变宽,选择最佳并购时机需要更多信息;在相对股价进入并购区域时,即可实施并购,否则,主并方的最佳策略为持有等待期权,即继续等待。研究结论可为企业选择最佳并购时机,尤其是国有企业选择产权转让的最佳时机提供直接理论指导和实践借鉴。     

灰色关联分析在最佳承包商选择中的应用

承包商选择方法是否科学合理直接关系到工程项目的成败.由于承包商选择方的主观性和承包商信息获取的不完备性,若采用传统选择方法,难以取得良好的效果,并最终影响到业主的利益.针对承包商信息的灰色特征,建立了承包商选择的灰色关联度决策模型,选用投标报价、施工方案、施工工期、质量水平和企业信誉作为5个主要评价指标,运用该模型并结合工程实例进行了灰色关联分析,获得了较为可靠的承包商排序,选出了最佳承包商,证明了该方法在最佳承包商选择中的可行性和有效性.旨在为承包商选择方提供一种简单、快捷而有效的评价方法,帮助承包商选择方做出综合和相对客观的评价.     

期权思想在多阶段项目投资中的应用

本文主要借助期权理论,讨论项目投资分多阶段进行时选择最佳投资的问题.首先通过在单阶段投资下建立项目投资的最佳选择框架,然后展开到项目投资分两个阶段进行的情形上进行讨论分析,得出此情形下的投资选择结论,最后把这一结论扩展到项目投资分多阶段进行的项目上.     

论珠算“优选法”

什么是“优选法”?就是事物最佳点的选择方法,广泛应用于生产、生活以及各行各业,如果应用于珠算,也就是珠算的最佳运算方法。我国著名科学家华罗庚于七十年代初来黑龙江省宣传过“优选法”,遗憾的是迄今     

广告媒体最佳选择的定量分析

本文应用线性规划问题的对偶单纯形法，分析广告媒体选择问题的最佳组合     

最优或次优组面试问题的最佳划分选择策略

本文研究了以选择绝对名次第一或第二的应聘者为目标的组面试问题的最佳停止规则,利用后退归纳法和边界阶段方法,获得最佳划分选择策略及确定两个边界阶段的最优不等式.     

基于改进模糊多准则决策法的弹性供应商选择及动态订单分配

本文通过选取具有风险抵抗能力的弹性供应商，解决因供应商稳定性低致使供应链风险的问题。首先，使用最佳-最差方法建立考虑风险因素初步选择供应商的模型。在此基础上，应用模糊多标准决策法建立多目标模型，解决考虑弹性标准的供应商动态选择问题。最后，运用改进狼群算法衡量利润和环境危害之间最佳的订单分配策略。以新能源汽车制造企业供应商选择及订单分配为例进行验证。结果表明，改进后的狼群算法与原始算法相比寻优精度更高、收敛速度更快，具有更好的综合性能。     

小样本下成本动因相关性的检验——以某固井公司运输作业为例

提高成本相关性的关键是提高成本动因的相关性.传统方法在成本动因选择方面依靠的是规范分析方法。样本匮乏是难以采用实证方法检验成本动因相关性的根本原因.本文通过引入部门ABC获取足够样本,采用实证检验方法研究成本动因的选择问题:首先,在实地获取第一手资料的基础上,通过规范分析,确定备选成本动因;其次,引入部门ABC获取足够的样本;最后,采用统计检验方法研究成本动因的相关性选择.研究发现,原有成本动因不是最佳成本动因;ABC方法确定的成本动因是最佳成本动因.     

提取医用黄腐酸的优化方案

本文介绍如何用正交试验法选择提取医用黄腐酸的最优方案 ,使提取出的医用黄腐酸达到最佳提取率 ,并符合国家药典标准     

计量经济模型的选择问题

在计量经济学的研究中,计量经济模型的选择问题是一个很重要的课题。本文把一般的计量经济模型化为线性统计模型,用模型参数的最佳线性无偏估计量作为模型选择的标准,从线性统计模型的角度讨论计量经济模型的选择问题。推断结果表明:计量经济模型的选择问题转化为已知矩阵的计算。     

校车安排问题

探讨如何安排校车运行使得教师和工作人员尽量满意的问题.首先建立动态规划模型和选址规划模型,求出合理站点位置及其总距离.然后用归一法定义满意度与距离的函数关系,考虑各区域人数,建立选址规划模型.得到合理站点位置和总满意度.之后建立双目标非线性规划模型,利用量纲分析法给出权重,以此求出合理乘车位置和满意度.最后对问题进行推...     

公交枢纽内始发线路优化配置模型及其模拟退火算法

城市公交枢纽由于用地规模有限、公交线路集中,其内部始发站的设置不同于一般的公交首末站.本文提出了公交枢纽内始发站的布置方法,建立了公交线路和站台间优化配置模型,并提出运用模拟退火算法对模型进行求解.最后通过实例分析了提出的优化模型及解法的有效性.     

A model for setting services on auxiliary bus lines under congestion

In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour). Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona.     

一类公交车调度问题的数学模型及其解法

本讨论了城市公交车调度问题中的上车乘客流分布和下车概率矩阵的处理方法，建立了基于模拟公共汽车运行的公交车调度问题的数学模型，给出了解法，并对模型的应用进行了讨论。     

电动公交枢纽直流快速充电模式及充电设施最优配置

发展电动公交能减少燃油消耗和城市污染物排放,对改善城市环境具有十分重要的意义.提出一种能显著减少电动公交运营成本的直流快速充电方式及相应的充电设施的建设模式.对公交枢纽直流快速充电模式下电动公交充电服务排队模型、高峰和平峰期充电设施最优配置模型进行了研究,并通过算例验证了这些模型的有效性.研究成果对我国电动公交的充电设施建设具有借鉴意义.     

校车站点及线路的优化设计

以高校新校区教师校车站点及线路安排为对象,首先针对乘车站点建立了双目标非线性规划模型,其中目标函数包括乘客到达站点的距离偏差最小与所有乘客到达站点的总的距离最小两个方面;站点确定后针对车辆数最少、车辆行驶的总距离最短、各辆车的运行距离均衡及各辆车的负荷均衡这4个目标建立针对线路优化的多目标非线性规划模型,并给出了解决这类问题的启发式优化算法.与目前国内外研究相比较,该模型与算法更实际,更具体的给出了问题的解答.     

A mathematical programming model for the bus deviation route problem

In small towns, or in those peripherical metropolitan areas in which the demand for public transportation is relatively low, the objectives of the bus route planner are different from those faced in highly congested networks. Some towns, also in Italy, are experimenting with urban public transportation systems where regular bus routes are designed which allow users located at specific points outside the main line to signal their presence to the bus driver, who then deviates from the main route to satisfy this demand. This way the bus line is a mixture between a regular line and a dial-a-ride system. The bus deviation route problem is concerned with the design problem which arises in planning the location of the demand points outside the line. A model is presented which takes into account both the advantage of passengers served by this deviation device and the disadvantage suffered by passengers on the bus, whose travel time increases during deviations, and by passengers downstream of the deviation whose waiting time also increases. Through some modeling assumption we are able to represent this problem as a mixed integer linear programming problem, whose relatively low dimension allows for exact solution through standard simplex-based branch and bound code. The proposed model has been applied to a real case and some results of this are presented and discussed.     

Metaheuristics approach for solving personalized crew rostering problem in public bus transit

The crew rostering problem in public bus transit aims at constructing personalized monthly schedules for all drivers. This problem is often formulated as a multi-objective optimization problem, since it considers the interests of both the management of bus companies and the drivers. Therefore, this paper attempts to solve the multi-objective crew rostering problem with the weighted sum of all objectives using ant colony optimization, simulated annealing, and tabu search methods. To the best of our knowledge, this is the first paper that attempts to solve the personalized crew rostering problem in public transit using different metaheuristics, especially the ant colony optimization. The developed algorithms are tested on numerical real-world instances, and the results are compared with ones solved by commercial solvers.     

公路客运监管的进化博弈分析

运用进化博弈理论研究公路客运监管问题,建立了公路客运监管问题的博弈模型,分析了公路客运车主和公路客运管理者之间的行为选择,得到了博弈方的复制动态方程,研究了博弈模型的进化稳定策略。探讨了影响进化稳定策略的因素。研究结果表明公路客运车主和公路客运管理者在有限理性基础上得到的进化稳定策略与博弈双方的收益、系统所处的初始状态有关,并根据所提出的博弈模型,提出了合理性建议。     

A model for the periodic optimization of bus dispatching times

We model the problem of dispatching time control in rolling horizons following a periodic optimization approach reactionary to travel time and passenger demand disturbances. This model provides more flexibility to transport planners allowing them to adjust the bus schedules during the daily operations. We prove that our periodic optimization model is a convex quadratic program, guaranteeing the global optimality of its solution. To reduce the computational burden, we introduce an iterative algorithm that uses gradient approximations to obtain an approximate dispatching solution. The proposed solution method is found to be significantly faster than exact optimization approaches for quadratic programming and maintains an (almost) negligible optimality gap in realistic bus operation scenarios. Finally, we show that our periodic optimization method outperforms myopic methods that adjust the dispatching time of each bus trip in isolation using operational data from bus line 302 in Singapore.