基于动态规划多期期货套期保值优化模型研究

通过对套期保值者头寸价值变化量的分析,采用动态规划方法,建立了多期套期保值动态模型,推导出多期套期保值进行动态跟踪调整的策略。该模型的特点一是反映了期货交易费用在套期保值中的作用,解决了现有期货套期保值策略忽略交易费用的不足,提高了模型的准确性。二是考虑保证金对期货套期保值的影响。把期货交易保证金的机会损失纳入套期保值策略内,从而使套期保值直接反映了期货保证金无利息收入、而存在机会成本的真实情况,弥补了现有研究不考虑期货交易保证金的机会损失的缺陷。三是体现了套期保值者收益最大化的原则。解决了现有模型只考虑了规避期货和现货组合的价格波动风险,忽略组合的收益的弊端,增加了模型的实用性和适用性。     

战略过程：一个基于决策的数理模型

以标准的战略管理过程模型为基础,将战略过程解释为战略状态的演变过程,其中战略状态变化被解释为战略决策和外生随机扰动共同作用的结果,应用随机动态规划模型化战略决策理性。结果表明,采用动态规划技术不仅可以确定战略状态的价值(竞争优势)与相应的最优战略制定决策和战略实施决策序列,还可以识别战略过程中的信息揭示对企业价值(竞争优势)的影响。这些结果在一定程度上逻辑一致地支持了战略管理中以理性决策为基本假设的设计学派和计划学派的观点。     

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.     

Optimizing the Collections Process in Consumer Credit

This paper builds a dynamic programming model to optimize the collections process in consumer credit. It determines which collections actions should be undertaken and how long they should be performed, including theoretical results about the form of the optimal policy under certain conditions. Finally, a case study is described based on data from the collections department of a European bank.     

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。     

利用和声分散搜索算法解决动态共乘的乘客选择研究

动态共乘作为一种配合解决城市交通出行难题的新模式近年来引起了人们越来越多的关注，然而在较大范围内选择合适的乘客，以便获得最佳的综合服务效果却具有相当大的挑战性。本文正是针对这一问题，建立了以乘客效用最大化和司机总行程最短为目标函数，以满足司机与乘客的时间要求和司机参与约束为限制条件的多目标0-1规划共乘模型，用于帮助司机选择最合适的乘客。根据该模型的特点，构造了加入了分散搜索机制的新的和声搜索算法。在仿真实验时，针对司机和乘客效用的两种产生方式，在较大规模的路网环境下利用该算法分别对模型进行了求解，得到了Pareto最优解集。仿真结果不仅表明了模型的合理性和算法的可行性，而且还指出基于效用函数可以发现更多合适的潜在乘客。最后，通过与文献中其它算法的对比进一步展示了本文算法的有效性。     

基于双层规划的反恐应急设施选址模型及算法

恐怖袭击常以人流密集地区的平民作为袭击目标，并存在突发性和随机性等特点，极易造成严重的袭击后果。通过反恐应急设施的合理布局可以缩短救援人员和物资的到达时间，从而减轻袭击后果。首先，对反恐应急设施选址问题进行描述，并将其构造为一类离散双层规划模型。其中，上层规划是关于政府选址的0-1规划问题，下层规划则是关于恐怖分子袭击目标选择的0-1规划问题。其次，结合模型和问题的特征设计算法，利用分支定界算法实现上层选址变量的隐枚举，同时通过下层问题的求解来确定上下界并判断是否满足分枝或剪枝的条件。最后，结合南疆地区的交通拓扑网络进行算例分析，结果证明有效的选址方案可以大大降低袭击损失。     

Sequence Independent Lifting in Mixed Integer Programming

We investigate lifting, i.e., the process of taking a valid inequality for a polyhedron and extending it to a valid inequality in a higher dimensional space. Lifting is usually applied sequentially, that is, variables in a set are lifted one after the other. This may be computationally unattractive since it involves the solution of an optimization problem to compute a lifting coefficient for each variable. To relieve this computational burden, we study sequence independent lifting, which only involves the solution of one optimization problem. We show that if a certain lifting function is superadditive, then the lifting coefficients are independent of the lifting sequence. We introduce the idea of valid superadditive lifting functions to obtain good aproximations to maximum lifting. We apply these results to strengthen Balas' lifting theorem for cover inequalities and to produce lifted flow cover inequalities for a single node flow problem.     

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。     

Bi-objective multi-resource scheduling problem for emergency relief operations

Abstract

Resource scheduling for emergency relief operations is complex as it has many constraints. However, an effective allocation and sequencing of resources are crucial for the minimization of the completion times in emergency relief operations. Despite the importance of such decisions, only a few mathematical models of emergency relief operations have been studied. This article presents a bi-objective mixed integer programming (MIP) that helps to minimize both the total weighted time of completion of the demand points and the makespan of the total emergency relief operation. A two-phase method is developed to solve the bi-objective MIP problem. Additionally, a case study of hospital network in the Melbourne metropolitan area is used to evaluate the model. The results indicate that the model can successfully support the decisions required in the optimal resource scheduling of emergency relief operations.