股票流动性与期望收益的关系研究

本文选取换手率作为股票流动性指标,采用FM两阶段截面回归方法研究了股票流动性与期望收益的关系。研究表明,我国股票市场流动性的波动较为稳定;股票流动性和期望收益的异常波动主要受政策的影响,但在周内的变化不存在系统性差异;上市公司的市场价值与股票收益无关;股票的流动性与期望收益负相关;投资者可以根据股票流动性与期望收益的关系套利。     

基于工期协调的项目公司与承包商收益激励模型

从项目公司和承包商双层角度,考虑项目公司通过显性收益激励契约手段与单一标段承包商之间就工期目标优化问题进行协调决策.假设决策过程是一个完全信息的动态博弈过程,基于博弈论并应用二层规划方法建立了以项目公司为主方、承包商为从方的Stackelberg主从递阶收益激励模型,采用逆向归纳法并引入拉格朗日函数对问题进行分情形讨论,设计了遗传算法求解该非线性规划问题的子博弈精练纳什均衡解.算例结果表明,项目公司通过提供一定的收益激励而非传统指令性手段促使承包商在可压缩范围内积极主动地去压缩项目工期,可以实现项目工期控制目标协调优化和双方收益目标的帕累托改善.     

基于异质性顾客心理期望等待时间的优先权服务定价研究

本文以非抢占式M/M/1排队系统为背景,以企业收益最大化为目标,基于顾客异质性(单位时间等待成本不同)将顾客分为两类,针对顾客的心理期望等待时间对服务提供商最优定价策略的影响进行研究。首先研究优先权顾客心理期望等待时间对企业收益的影响以及相应的优先权定价,然后研究优先权顾客和普通顾客同时存在心理期望等待时间对企业收益的影响和相应的优先权定价。研究表明:仅考虑优先权顾客的心理期望等待时间,企业应通过提高优先权定价来获得最优收益;当优先权顾客和普通顾客同时存在心理期望等待时间时,企业仍然采取提高优先权定价的策略,若普通顾客的价值大(获取服务的基本费用大),企业应对普通顾客提供一定的折扣来消除其心理期望等待时间增加企业收益;如果普通顾客的价值较小,企业应"有意"流失部分普通顾客,吸引更多顾客到优先权队列获取服务来获得更多收益。本文研究对于服务提供商在考虑顾客心理期望等待时间基础上设置最合理的队列机制有一定的指导意义和实际应用价值。     

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。     

含整变量非线性两层决策问题的一种求解方法

本文讨论一类含整变量的非线性两层决策问题.文中运用拉格朗日松弛技巧构造了两层问题的线性定界函数,针对上层决策变量全为一般整变量的非线性两层决策问题,提出了一种实用有效的求解方法.     

面向不确定多属性决策问题的范例检索算法研究

将不确定多属性决策问题转化为不确定性多属性范例的检索问题,利用范例推理方法获取最相似范例作对目标决策问题的近似解,通过范例修正缩短该近似解与目标决策问题解之间的差距直至完全一致.文章系统地提出了适合于不确定多属性问题检索要求的范例检索算法(RA-UMDM),重点研究了范例聚类、用基于梯形模糊集和改进的欧氏距离检索算法分别解决范例中模糊概念属性、区间特征属性的相似度计算问题.将该方法应用于两家医院临床辅助诊断决策过程求得了较为准确的解,并且基于范例库对RA-UMDM法的有效性、准确度、效率等进行了实验,结果表明该方法能够满足不确定多属性决策问题的检索要求,检索速度较快、质量高.     

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.     

基于二层规划的供应链契约谈判模型与求解

基于二层规划理论建立了一种形式化的契约谈判模型,并提供了基于模糊数学理论的交互式求解算法。以批量订货和价格折扣为例,分别研究了Stackclberg对策、集中式合作和基于二层规划的谈判合作三种策略下的契约机制。通过与另外两种策略的比较,初步得到采用谈判合作策略协调效果好、可执行性高的结论。     

Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences

In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the concept of efficiency with respect to preference information.     

基于委托-代理理论的股权激励模型的研究

在创业投资的运作过程中,建立有效的激励机制至关重要.把委托-代理博弈理论应用到创业投资的激励过程中,探讨了在考虑其它可观测变量情况下的博弈模型的求解程序及解的特征,在此基础上建立了最优股权激励模型,最后结合实例对结论进行了验证.     

An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations

This paper addresses the resource-constrained project scheduling problem with uncertain activity durations. An adaptive robust optimization model is proposed to derive the resource allocation decisions that minimize the worst-case makespan, under general polyhedral uncertainty sets. The properties of the model are analyzed, assuming that the activity durations are subject to interval uncertainty where the level of robustness is controlled by a protection factor related to the risk aversion of the decision maker. A general decomposition approach is proposed to solve the robust counterpart of the resource-constrained project scheduling problem, further tailored to address the uncertainty set with the protection factor. An extensive computational study is presented on benchmark instances adapted from the PSPLIB.     

Linear solution schemes for Mean-SemiVariance Project portfolio selection problems: An application in the oil and gas industry

We study the Mean-SemiVariance Project (MSVP) portfolio selection problem, where the objective is to obtain the optimal risk-reward portfolio of non-divisible projects when the risk is measured by the semivariance of the portfolio׳s Net-Present Value (NPV) and the reward is measured by the portfolio׳s expected NPV. Similar to the well-known Mean-Variance portfolio selection problem, when integer variables are present (e.g., due to transaction costs, cardinality constraints, or asset illiquidity), the MSVP problem can be solved using Mixed-Integer Quadratic Programming (MIQP) techniques. However, conventional MIQP solvers may be unable to solve large-scale MSVP problem instances in a reasonable amount of time. In this paper, we propose two linear solution schemes to solve the MSVP problem; that is, the proposed schemes avoid the use of MIQP solvers and only require the use of Mixed-Integer Linear Programming (MILP) techniques. In particular, we show that the solution of a class of real-world MSVP problems, in which project returns are positively correlated, can be accurately approximated by solving a single MILP problem. In general, we show that the MSVP problem can be effectively solved by a sequence of MILP problems, which allow us to solve large-scale MSVP problem instances faster than using MIQP solvers. We illustrate our solution schemes by solving a real MSVP problem arising in a Latin American oil and gas company. Also, we solve instances of the MSVP problem that are constructed using data from the PSPLIB library of project scheduling problems.     

需求预测综合模型及其与库存决策的集成研究

准确的预测有助于企业做出有效的决策,包括生产计划、定价和促销决策等,以减少库存、提高客户满意度和企业竞争力． 以快速消费品为研究对象,分析其需求影响因素,建立了时间序列分析与多元回归整合的需求预测综合模型; 将此预测模型引入到库存决策中,构建了基于库存成本最小的需求预测与库存决策集成模型,并借助变邻域搜索算法获得模型的参数值; 最后,选用实际数据,验证了所构建的需求预测综合模型、物流需求预测与库存决策集成模型及其求解方法的有效性．     

An EOQ inventory model for items with Weibull distribution deterioration,ramp type demand rate and partial backlogging

In this paper, an EOQ inventory model is presented depleted not only by demand but also by Weibull distribution deterioration, in which the demand rate is assumed that with a ramp type function of time. In the model, shortages are allowed partial backlogging and the backlogging rate is variable and is dependent on waiting time for the next replenishment. The method is illustrated by three numerical examples, and sensitivity analysis of the optimal solution with respect to parameters of the system is carried out.     

An integrated production and inventory model for a whole manufacturing supply chain involving reverse logistics with finite horizon period

This paper proposes a model and solution method for coordinating integrated production and inventory cycles in a whole manufacturing supply chain involving reverse logistics for multiple items with finite horizon period. A whole manufacturing supply chain involving reverse logistic consists of tier-2 suppliers supplying raw materials to tier-1 suppliers, tier-1 suppliers producing parts, a manufacturer which manufactures and assembles parts from tier-1 suppliers into finished products, distributors distributing finished products to retailers, retailers selling products to end customers and a third party which collects the used finished products from end customers, dissembles collected products into parts, and feed the parts back to the supply chain. In this system, we consider a finite horizon period. A mathematical model for representing the behaviors of the system is developed. Solution methods based on decentralized and a combination of decentralized and centralized decision making process, referred to as the semi-centralized decision making process, are proposed to solve the model while the centralized decision making process is solved by a mixed integer nonlinear programming method. A numerical example is used to demonstrate the model and the solutions based on the three types of the coordination.