基于MATLAB仿真的浴缸水温控制策略分析

一个合理的加水策略,既能使浴缸中的水长时间保持恒定的舒适温度,又能尽可能节约水.综合考虑影响浴缸水温的各种因素,通过浴缸热传导模型和多目标规划模型,求解包含加水时间、流速等信息的最优加水策略.     

2016年美国大学生数学建模竞赛题目

问题A:热水澡 人们经常会通过用一个水龙头将浴缸注满热水,然后坐在浴缸里清洗和放松.这个浴缸不是带有二次加热系统和循环喷流的温泉式浴缸,而是一个简单的水容器.过一会儿,洗澡水就会明显变凉,所以洗澡的人需要不停地从水龙头注入热水,以加热洗浴的水.该浴缸的设计是这样一种方式,即当浴缸里的水达到容量极限时,多余的水就会通过溢水口流出.考虑空间和时间等因素,建立一个浴缸的水温控制模型,以确定最佳策略,使浴缸里的人可以利用这个策略让整个浴缸中的水保持或尽可能接近初始的温度,而且不浪费太多的水.     

洗衣机节水的数学模型

基于最优化原理建立了对常用洗衣机普遍适用的节水模型 ,给出了在满足一定洗涤效果的条件下 ,最优的洗衣机加水次数与每次的加水量 .     

电热耦合综合能源系统双阶段多目标规划研究

多能耦合系统是未来分布式能源供给方式的重要发展方向。为了实现电热耦合能源供给系统的合理规划、促进能源供给与消费的经济与环保的协调发展,提出一种面向电热耦合能源系统的综合能源系统双阶段规划优化方法。模型的第一阶段是在投资和环境最优的目标下实现电热耦合综合能源系统的合理规划,第二阶段是在考虑设备运行特性的基础上对规划的结果进行运行优化,以获得能源系统的最优运行方案,并从多个指标验证规划方案的合理性。利用NSGA-II算法求得模型进的帕累托解集,使用多准则妥协优化法从帕累托解集中决策出最优配置方案。仿真结果表明,提出的双阶段多目标综合能源规划方法能够实现能源供给系统的经济与环保双优。     

赞比西河水资源调度

研究了赞比西河水资源的调度决策问题。赞比西河上的卡里巴大坝年久失修,赞比西河管理局给出了3种方案:维修、重建或用多个大坝代替现有的卡里巴大坝。通过查阅赞比西河相关资料及沿岸的地形地貌信息,首先确定了11个大坝的地理位置及每个大坝发电机组的装机容量,目标是满足水库附近居民及工农业的用水和用电需求;其次,根据投入产出比对管理局提出的3种方案进行了评价,以确定最优决策方案;最后,基于多坝替代系统建立了梯级水库的水资源调度模型,利用坐标轮换方法分别对平水年、丰水年和枯水年进行了水资源调度。模型的敏感性分析表明调度方案模型是稳健的,建立的调度模型符合实际,使得多坝系统水管理能力增强。     

双瓶颈路段家庭出行者早高峰出行问题研究

针对一次连续出行中两个路段各存在一个瓶颈的双瓶颈路段,研究了家庭出行者早高峰期间先后经过双瓶颈到达学校和工作地的出行行为。首先建立了无收费下的用户均衡模型,接着考虑了拥挤收费模型,并就学校工作地开始时间差值大小的不同展开讨论,分析得出对应系统总出行成本最优时的收费值和收费时窗。研究发现收费管理能够有效降低系统总成本,并且学校和工作地开始时间差较小时的系统总成本更低,最后,通过数值算例验证了高峰时长保持不变,且得出了使得系统出行成本最优时的收费方案。     

无人机协同任务的优化方案

研究的是多架无人机协同完成侦察、中继等作战任务的方案优化问题.对于侦查任务,首先建立了以总行进路径最短为目标的非线性0-1规划模型,求得单架加载S-1无人机无法完成任务,故又建立了以两组行进路径之和最短和组间路程差最小为目标函数的目标群分组的非线性0-1规划模型,得到最优分组方案.然后,由于S-2的扫描范围广,无需行遍所有目标点即可完成任务,故建立以扫描所有目标点为约束条件,遍历点数最少为目标的非线性0-1规划模型,求得仅需经过18个点即可完全扫描所有68个目标点.接下来,在满足S-1和S-2扫描每个目标点的时间差小于4h的前提下,得到了最优的飞行方案.对于中继任务,通过调整无人机的起飞时间,减少通过雷区的任意两架无人机的位置差异,得到仅需1架中继无人机的最优飞行方案.     

基于语言值软集的多准则群决策方法及其应用

在语言值评估集上引进适当的运算,建立语言值逻辑代数系统,并利用虚拟术语指标不丢失信息的特点,扩展语言值逻辑代数系统为连续语言值逻辑代数系统。通过加权平均算子将全部专家对各决策方案的语言值评估信息集结,得到专家群对全部决策方案就全部准则的集中评估,全部集中评估值构成决策方案上的语言值软集。建立优化模型计算最优准则权重,利用最优准则权重将专家关于各准则的语言值评估结果进行集结,得到各专家对全部决策方案的评估值,评估值全体可看成专家群上的语言值软集,这里参数集为决策方案集。建立基于决策方案上的语言值软集的粗糙近似模型——语言值粗糙近似模型,通过计算各专家对全部决策方案的评估值关于语言值粗糙近似模型的下近似和上近似,得到专家群上的语言值下近似软集和上近似软集。通过对全部决策方案评估集及其语言值粗糙下近似、上近似进行加权算术平均,分别得到三个决策方案上的语言值模糊集。通过三个语言值模糊集对全部决策方案排序。最后,应用基于语言值软集的多准则群决策方法对电子商务监管系统安全进行多准则综合决策评估,说明本文提出的多准则群决策方法是有效的和合理的。     

基于变权系数的人才聘用模型

主要是将招聘模型化成标准的指派问题,运用匈牙利算法进行处理.模型一:通过设置一虚拟部门通过上述方法得到最优分配方案.模型二:构建了偏差函数与变权函数,同样构造成一指派问题,得到七种分配方案,然后从中找出最优解.此模型还可推广到多人应聘多个部门的模型.     

时变需求等量进货情形下集成供应链生产订货策略研究

构建了一个包含原料采购、生产和销售过程的集成供应链模型,研究了由原料、生产商和销售商产品构成的三层库存系统的生产订货问题。在有限的规划期内,销售商每次进货量相同,生产商按照EOQ模型采购原材料。以最小化供应链系统的总运营成本为目标,构建一个混合整数非线性规划模型,寻找销售商最优订货方案和生产商最佳生产策略。首先利用网络优化方法求解生产商的最优生产计划,其次利用定界穷举法寻求销售商最优的订货周期,给出了具体的计算方法和Matlab程序。通过算例分析验证了算法的有效性,并研究了各参数对最小费用及最优解的影响。     

供应中断风险下采购与定价决策分析

供应中断是供应链上的企业可能面临的问题,运用合理的采购策略可以帮助企业有效缓解供应中断风险。本文研究了供应中断下供应商和制造商之间的纵向竞争和两个制造商之间的横向竞争问题。供应商制定批发价,两个制造商采用不同的采购策略进行产量博弈,其中一个制造商采用紧急双源订货策略,另一个采用可靠单源订货策略。论文采用了多阶段博弈模型,分析了制造商之间的合谋与竞争两种行为,求出了供应商和制造商的最优决策,比较了这两种行为对供应商和制造商的影响。通过数值分析,讨论了成本参数和可靠性参数对于最优订货量的影响以及对于采用不同订货策略的制造商期望利润的影响。     

价格和服务双因素影响的供应链协调决策模型研究

以单个制造商和存在竞争的两个零售商组成的供应链结构模型为研究对象,建立价格和服务两个重要因素影响的市场需求函数,研究供应链协调决策模型。以销售价格、服务质量和制造商批发价格作为三个决策变量,分析集中决策和分散决策两种情景的最优策略,研究收益共享、服务成本分担、收益共享成本分担等三种不同契约的供应链协调问题,并使用数值仿真方法,分析了相关参数变化对系统协调的影响。仿真结果表明:收益共享契约和成本分担契约需满足一定条件才能达到供应链协调,但其效果不一定实现帕累托最优;收益共享和成本分担契约可实现供应链协调,但收入共享系数需在合理区间取值;改进的收益共享成本分担契约能够避免共享系数的盲区,更加有效地达到供应链协调,保持供应链良好运行。     

Supply chain scheduling: Sequence coordination

A critical issue in supply chain management is coordinating the decisions made by decision makers at different stages, for example a supplier and one or several manufacturers. We model this issue by assuming that both the supplier and each manufacturer have an ideal schedule, determined by their own costs and constraints. An interchange cost is incurred by the supplier or a manufacturer whenever the relative order of two jobs in its actual schedule is different from that in its ideal schedule. An intermediate storage buffer is available to resequence the jobs between the two stages. We consider the problems of finding an optimal supplier's schedule, an optimal manufacturer's schedule, and optimal schedules for both. The objective functions we consider are the minimization of total interchange cost, and of total interchange plus buffer storage cost. We describe efficient algorithms for all the supplier's and manufacturers’ problems, as well as for a special case of the joint scheduling problem. The running time of these algorithms is polynomial in both the number of jobs and the number of manufacturers. Finally, we identify conditions under which cooperation between the supplier and a manufacturer reduces their total cost.     

Optimum Burn-in Time for a Bathtub Shaped Failure Distribution

An important problem in reliability is to define and estimate the optimal burn-in time. For bathtub shaped failure-rate lifetime distributions, the optimal burn-in time is frequently defined as the point where the corresponding mean residual life function achieves its maximum. For this point, we construct an empirical estimator and develop the corresponding statistical inferential theory. Theoretical results are accompanied with simulation studies and applications to real data. Furthermore, we develop a statistical inferential theory for the difference between the minimum point of the corresponding failure rate function and the aforementioned maximum point of the mean residual life function. The difference measures the length of the time interval after the optimal burn-in time during which the failure rate function continues to decrease and thus the burn-in process can be stopped.      

考虑破产惩罚的对偶风险模型的最优控制

本文主要研究对偶风险模型的最优控制问题. 为了考虑破产对保险公司(金融机构)的影响, 我们在构造价值函数的过程中引入了一个变量来测度破产对公司盈利的影响. 为了求得最优的控制策略, 我们首先研究了两类带有约束的优化问题. 基于这些带约束优化问题的解, 我们给出了无约束的最优策略.     

通胀市场下的风险补偿在线租赁策略设计

考虑到实际租赁市场中设备的租赁和购买价格随着时间推移持续上涨的特征,研究了通货膨胀市场中的租赁问题在有利率情形下的在线竞争策略,并建立了相应的概率预期的风险补偿模型。首先运用在线算法和竞争分析理论设计了该问题的最优竞争策略,并给出最优竞争比。接着,在风险补偿竞争分析框架下,进一步讨论该问题,投资者可以控制风险,根据自己不同的风险容忍度和未来预期选择补偿最大的租赁策略;也可以根据给定的补偿收益约束选择风险最小的策略。最后通过数值分析,验证了相关结论的正确性,也表明了基于概率预期的风险补偿策略大大改善了该租赁问题的竞争比性能。     

On optimal operating conditions for a data processing system: A stochastic approach

In this paper, we consider the problem of determining optimal operating conditions for a data processing system. The system is burned‐in for a fixed burn‐in time before it is put into field operation and, in field operation, it has a work size and follows an age‐replacement policy. Assuming that the underlying lifetime distribution of the system has a bathtub‐shaped failure rate function, the properties of optimal burn‐in time, optimal work size and optimal age‐replacement policy will be derived. It can be seen that this model is a generalization of those considered in the previous works, and it yields a better optimal operating conditions. This paper presents an analytical method for three‐dimensional optimization problem. An algorithm for determining optimal operating conditions is also given. Copyright © 2007 John Wiley & Sons, Ltd.     

Static-arbitrage optimal subreplicating strategies for basket options

In this paper we investigate the possible values of basket options. Instead of postulating a model and pricing the basket option using that model, we consider the set of all models which are consistent with the observed prices of vanilla options of all strikes. In the case of basket options on two components we find, within this class, the model for which the price of the basket option is smallest. This price, as discovered by Rapuch and Roncalli, is associated to the lower Fréchet copula. We complement their result in this paper by describing an optimal subreplicating strategy. This strategy is associated with an explicit portfolio which consists of being long and short a series of calls with strikes chosen as the zeros of an auxiliary function.     

Manufacturer cooperation in supplier development under risk

Supplier development involves efforts undertaken by manufacturing firms to improve their suppliers’ capabilities and performance. These improvement efforts can be targeted at a variety of areas such as quality management, product development, and cost reduction. Since supplier development requires investments on the part of the manufacturer, it is important to optimally allocate investment dollars among multiple suppliers to minimize risk while maintaining an acceptable level of return. This paper presents a set of optimization models that address this issue. We consider two scenarios: single-manufacturer and multiple suppliers (SMMS) and two-manufacturer and multiple suppliers (TMMS). In the SMMS case, we suggest optimal investments in various suppliers by effectively considering risk and return. The TMMS case investigates whether manufacturers with differing capabilities could gain risk reduction benefits from cooperating with each other in supplier development. Through illustrative applications, we identify conditions in which both cooperation and non-cooperation are beneficial for manufacturers. Under conditions of cooperation, we propose optimal investments for manufacturers to achieve high levels of risk reduction benefits.     

A robust optimization approach to experimental design for model discrimination of dynamical systems

A high-ranking goal of interdisciplinary modeling approaches in science and engineering are quantitative prediction of system dynamics and model based optimization. Quantitative modeling has to be closely related to experimental investigations if the model is supposed to be used for mechanistic analysis and model predictions. Typically, before an appropriate model of an experimental system is found different hypothetical models might be reasonable and consistent with previous knowledge and available data. The parameters of the models up to an estimated confidence region are generally not known a priori. Therefore one has to incorporate possible parameter configurations of different models into a model discrimination algorithm which leads to the need for robustification. In this article we present a numerical algorithm which calculates a design of experiments allowing optimal discrimination of different hypothetic candidate models of a given dynamical system for the most inappropriate (worst case) parameter configurations within a parameter range. The design comprises initial values, system perturbations and the optimal placement of measurement time points, the number of measurements as well as the time points are subject to design. The statistical discrimination criterion is worked out rigorously for these settings, a derivation from the Kullback-Leibler divergence as optimization objective is presented for the case of discontinuous Heaviside-functions modeling the measurement decision which are replaced by continuous approximations during the optimization procedure. The resulting problem can be classified as a semi-infinite optimization problem which we solve in an outer approximations approach stabilized by a suggested homotopy strategy whose efficiency is demonstrated. We present the theoretical framework, algorithmic realization and numerical results.