基于半离差风险收益的投资组合管理优化模型研究

本文在对投资组合管理理论分析的基础上,利用半离差法计算组合投资的风险与收益,克服了H. Markowitz提出的均值一方差模型研究的不足以及半方差模型的烦琐,提出了基于半离差风险收益的多目标优化模型;假设投资组合一般包括三种资产形式:股票、债券、现金。引进了机会成本概念在投资选择中的重要性,更加符合我国投资者的实际,便于操作,这为证券投资组合优化提供了一种新的方法,并有一定的参考借鉴价值。     

基于差分的数量折扣条件下订货策略优化模型

通过采用合适的数量折扣策略,供需双方都可以提高自己的利润。用双层规划模型描 述了供应链管理中供应商与订货商合作情况下确定数量折扣及订货量问题,并用基于差分的 算法进行了求解. 实例分析说明双方合作的双层规划模型能正确表示实际的供需关系,在平衡 点可以使双方利益均达到最大     

基于协同效应的知识创新团队伙伴选择方法

在知识创新团队的伙伴选择问题中着重考虑了伙伴间的协同效应信息。首先,分析了伙伴之间的协同关系与协同效应,描述了考虑多个协同效应评价指标的知识创新团队伙伴选择问题;然后,建立了团队伙伴选择的数学模型,该模型是一个0-1二次整数规划问题,为了求解该问题,开发了一种GRASP启发式算法;最后,通过一个实例分析说明了所提出方法的可行性和实际应用价值。     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

Optimizing global thermal coal shipments

Thermal coal is used to produce energy; with changing emissions standards and advents in renewable technology, the thermal coal market has seen significant transformation over the past decade. We develop a mixed-integer optimization problem that seeks to minimize shipment costs while meeting demand for thermal coal, and which respects quality constraints, supply limits, and port capacity; we use this model to analyze the following scenarios: (i) a counterfactual setting in which we compare historical shipping patterns to model results using a 2012 base year; (ii) the explicit effect of Chinese mandates on coal shipments; (iii) the impact on our shipping patterns of reduced Chinese and Indian demand; (iv) the effects of the Baltic Dry Index and oil prices; and (v) a comparison of shipments prior and subsequent to Panama Canal expansion. Our work can be used to inform policy, study responses to variable price and demand scenarios, and provide insight to both coal producers and consumers about the international coal market. For example, removal of mandates set by the Chinese government to fill its own demand decreases coal flows from Northern to Southern China by 56%, which has a spill-over effect on European and American markets; and, expansion of the Panama Canal leads to only modest shipping increases through the canal (6.7%), with more coal originating from Colombia serving Asian demand.     

社区应急疏散动态协作调度优化研究

针对灾民数量和路网通行时间的动态性以及灾民疏散反应系数的随机性,本文提出了社区应急疏散协作调度优化流程,并以疏散灾民数量最大化和疏散成本最小化为目标,构建了社区应急疏散多种运输方式协作调度优化模型,并给出了求解该模型的改进多目标遗传算法。然后,论文使用Tansmodeler模拟社区应急疏散协作调度优化过程,加载疏散灾民动态需求和历史出行时间表,并对模型和算法进行验证。结果表明,该模型和算法可以在有效刻画疏散灾民数量和路网通行时间的基础上,为不同时刻的交通工具配置及疏散路径选取提供决策。     

改进区间可接受度的证券投资组合区间二次规划模型

本文首先基于Markowitz的经典均值方差模型,针对不确定环境下的投资组合问题,把证券的收益率、风险损失率和流动性用区间数描述,建立了一种新的含交易成本的证券投资组合区间二次规划模型。其次,为求解该模型,提出了改进的区间可接受度确定性转换方法,通过引入优化水平α与可接受水平η将不确定二次规划转化为确定型规划。最后,通过数值实验将提出的方法与传统方法进行比较,结果表明本文所提出的方法与模型具有相对较好的可行性与实用性。     

基于知识量的知识作业评测研究

以知识量作为作业难度表征的重要指标;在讨论信息量、教学时间与知识量关系的基础上,根据BROOKES信息基本方程,建立了社会标准教学时间与知识量的映射关系;根据知识表达系统提出了基于社会标准教学时间的知识测度原理及其测度方法;结合岗位知识量的测度进行了算例说明.     

基于区间灰色区间数的多准则决策方法

将灰色模糊数扩展,定义了区间灰色区间数及其距离.针对准则值为区间灰色区间数的信息不完全的多准则决策问题,提出了一种基于目标规划法的灰色模糊多准则决策方法,求得最优权重向量,从而得到各方案的排序.最后给出一个算例说明方法的可行性和有效性.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.