基于资源分配的MIS项目选择模型及其应用

本文论述了MIS项目选择问题的重要性, 对常用的MIS项目选择方法进行了综合分析。为克服常用方法的缺陷即无力解决具有资源约束的、多目标相互冲突且计量单位不可比的MIS项目选择问题, 本文提出了MIS项目选择的目标规划模型。最后, 本文以某公司的数据对模型进行了上机运行, 运行结果与应用常用方法所得结果比较表明, 目标规划法是MIS项目选择的较满意方法。     

资源分配问题两层优化分析的元模型方法

资源分配问题有着广泛应用,它的经典数学模型是线性规划问题。实际应用中资源的拥有量允许在一定范围内变化,资源分配优化所追求的应当是单位资源成本上的利润最大化。针对这一问题,提出了两层优化分析模型,并利用元模型给出了求解的方法。用二阶多项式元模型代替低层的较复杂的优化分析模型,将它嵌入到高层模型,可以实现快速可行的决策支持。数值实验结果表明了该方法的有效性。     

农业开发小区的优化设计模型

本以绥化市１３１农业开发小区为研究对象，建立线性规划模型，合理利用现有的水土资源和自然条件，以增加粮、鱼、肉的产量，增强农业开发发劲为目标，以改造中低产田，开垦宜农荒地为重点，达到水，林、田、路的综合治理，使小区的投资最低，效益最好。     

供应链中二级分销网络优化设计的随机规划模型

给出供应链中二级分销网络优化设计的机会约束规划模型。模型中将各个分销中心的需求量和各工厂的生产能力设为随机参数，并进一步讨论如何将模型中的机会约束转化为确定性等价类问题。     

考虑感知满意度的多受灾点应急资源分配模型

在大规模突发事件应急物资调度决策中,由于时间的紧迫性和资源的竞争性,合理、有效地进行应急资源分配成为亟待解决的关键问题。考虑到人是有限理性的,在前景理论的基础上,建立了应急响应时间的感知满意度函数以衡量灾民对救援响应时间的满意程度,并将量化后的时间满意度、需求满意度和效用满意度作为模型的3个目标函数,构建了一个多目标非线性整数规划模型描述大规模突发事件发生后的初始阶段应急物资分配问题。最后,通过分散搜索算法对模型求解,给出算例证明了模型的有效性。     

分布式实时系统的低能耗资源分配方法研究

针对基于动态电压调整技术的调度算法在任务切换时大幅度的频率调整给系统带来较多的额外能耗这一问题,提出了一种均匀化任务利用率的启发式资源分配方法。该方法选用时间Petri网对分布式实时系统建模,并根据时间Petri网状态空间的变化规律,简化系统状态空间的生成过程,提高了资源分配算法的实现效率。实验表明,上述方法能够降低目标系统频率调整带来的系统能耗开销。     

基于消费主体行为的有限公共服务资源分配模型

考虑消费主体行为对有限公共服务资源分配的影响,提出了基于前景理论的有限公共服务资源分配决策模型及求解算法。将消费主体行为表征为满意度和价值函数两方面,定义了同一消费主体面临不同分配方案下获得资源数量的满意度和同一方案下不同消费主体相互比较而获得的满意度并进行组合,同时,基于前景理论定义了满意度的价值函数;其次,以综合前景值最大为目标构建非线性优化模型,并设计模型求解的算法;最后通过实例说明了方法的有效性和可行性。     

基于博弈论健壮性增强的资源分配模型

如何保障用户QoS是动态、不确定网格环境中资源分配面临的一个新问题.针对网格资源的不可靠性特点,提出了健壮性增强的作业执行服务的概念及其确定方法,基于该概念提出了健壮性增强的离线资源分配模型,通过将作业执行服务中对应的多个网格节点资源分配给作业冗余执行以增强其健壮性.基于该模型将资源分配描述为一个非合作博弈过程,求得了帕累托最优分配方案,并提出了一种健壮性增强的离线资源分配策略.实验结果表明:该分配模型兼顾了效率和公平, 增强了作业执行的健壮性,并较好地评估资源的信任行为.     

井下机车运输调度的资源分配模型及无死锁优化调度

对井下机车运输系统进行无死锁调度和性能优化, 首先, 建立三种不同调度策略下的资源分配Petri网模型, 设计对应调度策略下无死锁标识的最大边界设置算法, 证明了调度策略在最大标识边界设置下的无死锁性. 然后, 以最小化时耗和能耗为优化目标, 利用遗传算法, 采用变迁标号的自然编码方式, 通过检查变迁的引发条件检测染色体的可行性, 修复不可行的染色体使其对应的调度满足资源约束, 从而保证了算法所利用的所有染色体均可对应系统的可行调度, 最后进行实例仿真. 设计的无死锁调度的最大标识边界设置算法和遗传算法为井下机车的运输调度提供了可靠的理论基础.     

产品维修性设计的系统工程方法

为了在产品设计中系统、全面、准确地反映用户需求,提高维修性要求与产品设计特征之间的关联性,提出维修需求到维修性要求再到产品设计特征的规范化映射方法。通过对用户需求陈述的处理和基于启发式问题的分析,进行用户需求识别;基于系统工程方法,展开维修性设计分析;运用质量功能展开法,进行用户需求向设计要素的转换。将该方法用于某无人机通用操控席位的操作台维修性设计,为生成符合用户需求的系统布置方案提供了权衡依据,在减少设计差错的同时提升了需求转换的精度与效率,验证了方法的可行性。     

Product design on the basis of fuzzy quality function deployment

In the implementation of quality function deployment （QFD）, the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that should trade off, and optimize all kinds of conflicts and constraints. A fuzzy linear programming model （FLP） is proposed. On the basis of the inherent fuzziness of QFD system, triangular fuzzy numbers are used to represent all the relationships and correlations, and then, the functional relationships between the customer needs and engineering characteristics and the functional correlations among the engineering characteristics are determined with the information in the house of quality （HoQ） fully used. The fuzzy linear programming （FLP） model aims to find the optimal target values of the engineering characteristics to maximize the customer satisfaction. Finally, the proposed method is illustrated by a numerical example.     

Hybrid particle swarm optimization for multiobjective resource allocation

Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.     

System deployment optimization in architecture design

Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.     

Resource allocation with minimum transmit power in multicast OFDM systems

To minimize the total transmit power for multicast service in an orthogonal frequency division multiplexing (OFDM) downlink system, resource allocation algorithms that adaptively allocate subcarriers and bits are proposed. The proposed algorithms select users with good channel conditions for each subcarrier to reduce the transmit power, while guaranteeing each user’s instantaneous minimum rate requirement. The resource allocation problem is first formulated as an integer programming (IP) problem, and then, a full search algorithm that achieves an optimal solution is presented. To reduce the computation load, a suboptimal algorithm is proposed. This suboptimal algorithm decouples the joint resource allocation problem by separating subcarrier and bit allocation. Greedy-like algorithms are employed in both procedures. Simulation results illustrate that the proposed algorithms can significantly reduce the transmit power compared with the conventional multicast approach and the performance of the suboptimal algorithm is close to the optimum.     

基于灵敏度分析的系统可靠性稳健分配优化方法

在系统可靠性分配中,考虑单元可靠度的不确定性已是可靠性分配的现实需要.为了提高系统可靠性分配优化的质量,将稳健理论引入可靠性分配中,提出基于单元可靠性灵敏度的系统可靠性稳健分配方法.将单元可靠性灵敏度溶入系统可靠性分配模型之中,建立系统可靠性稳健分配模型.在此基础上,采用粒子群-序列二次规划算法对该模型进行优化设计,该混合算法既保持了粒子群算法全局收敛的特点,又补充了序列二次规划法精确求解的能力,因此该混合算法可以快速获取全局最优解.通过对发动机曲柄连杆机构进行可靠性稳健分配设计,验证了可靠性稳健分配模型的合理性和混合算法的寻优能力.对结果分析表明,所提方法可以较好解决单元可靠度不确定时的可靠性分配问题,混合算法具有较强的全局搜索能力,分配优化结果具有较强的稳健性.     

智能ICAQFD 系统中HOQ 多目标优化模型关键技术研究

产品质量表示产品的质量特征(PQC)在其整个生命周期内满足用户需求(VOC)的程度,提高产品质量、迅速开发出满足用户需求的产品是企业生存的关键.虚拟原型逼真设计主要研究虚拟环境下的产品建模问题以及基于仿真的集成产品和过程设计问题,能有效地提高企业的市场竞争力.智能计算机辅助质量功能配置(ICAQFD)模型是虚拟原型逼真设计实现的关键技术之一.在论述ICAQFD系统实现的几个关键技术的基础上,针对质量屋(HOQ)中的决策问题是一复杂的多变量、多目标决策过程的特点,研究了模糊环境下HOQ多目标优化模型实现的关键技术,建立了基于HOQ信息的PQC(产品质量特征)技术先进度的模糊线性规划(FLP)模型和基于模糊回归分析的PQC目标值的FLP模型,结合应用实例,验证了模型的有效性.     

基于模糊随机规划的反TBM目标分配优化模型

针对反导目标分配优化问题中存在的不确定性特征,引入模糊随机规划理论.首先建立了基于模糊随机规划的反战术弹道导弹(tactical ballistic missile,TBM)的目标分配优化模型.在此基础上,构建了一种针对多约束目标分配问题的粒子编码方案,并改进传统粒子群算法的位置和速度更新方式,提出了改进型离散粒子群(improve discrete particle swarm optimization,IDPSO)算法.最后,设计了模糊随机模拟技术和IDPSO算法相结合的混合智能求解算法.仿真实例表明,混合智能算法全局寻优能力强,优化效率高,满足反TBM目标分配优化对时效性的要求.     

New product design strategies with subsidy policies

Industrial development can enrich people’s lives,but it also causes environmental pollution,which is an area of significant concern among governments,consumers,and companies.Governments formulate some environmental policies,which motivate industry by providing greater incentives for green product development.Consumers are classified into two groups - ordinary and green market segments - according to their environmental awareness and attitudes.In this regard,companies need to reconsider their primary product design strategies.By investigating the interactions among customers’ preferences,firms’ product strategies,and government subsidy policies,this paper presents a theoretical model for new product design strategies.After detailed theoretical analysis of such strategies,we found that to motivate firms to choose environmentally friendly product design strategies, governments should inaugurate effective subsidy policies.After simultaneously considering environmental issues and firms’ benefits,we designed a subsidy policy.With such a policy,firms can change their primary product design strategies and develop both green and ordinary products,thereby increasing the firms’ profits and improving the total environmental quality.