非线性整数规划的蚁群算法

提出了一种新的蚁群算法来求解无约束的整数规划问题,蚂蚁在整数空间内运动,同时在路径上留下激素,以此引导搜索方向。对蚁群算法参数的合理选取进行了实验分析,给出了算法参数选取的基本原则。数值试验计算结果表明:该方法比较有效,并具有通用性。     

供应链二级分销网络生产计划双层模糊机会约束规划模型

从供应链的集成和协作角度出发,提出了在模糊环境下二级分销网络生产计划制定的双层模糊机会约束规划模型,并根据可能性理论将之清晰化.然后采用模糊交互式决策方法将二层规划问题化为一层来求解,并给出了一个数值算例.     

机会约束规划在地对空雷达干扰资源优化分配中的应用

应用机会约束规划理论,研究了反空袭作战中地对空雷达干扰资源优化分配问题。首先,在给出雷达威胁等级判定模型的基础上,利用干扰压制区建立了地对空雷达干扰效果评定模型。其次,根据所建干扰效果评定模型,综合考虑干扰资源分配过程中存在的不确定因素,建立了双层模糊机会约束混合整数规划模型。最后,利用可能性测度理论,将干扰资源优化分配模型清晰化为双层混合整数规划模型,通过求解混合整数线性规划来获取优化分配模型的最优解。仿真算例表明:所建的干扰资源优化分配模型不仅能够有效处理分配过程中的不确定信息,而且能够在本级干扰效果最大化的同时实现全局最优化;模型的求解算法针对性更强,非常适合求解该问题。     

分式型模糊整数规划

本文给出了分式型模糊整数规划的定义,并将目标函数为分式型模糊整数规划转化为一般的目标模糊整数规划,再将它转化为清晰的线性规划,同时给出求解方法。     

模糊需求环境下多产品采购配额优化模型

建立了模糊需求和价格折扣并存条件下多产品采购配额分配问题的模糊多目标混合整数规划模型.针对该模型的特点,提出了如下求解策略,即借助于隶属度函数,首先将模型中的模糊目标和模糊约束条件清晰化;然后,通过最大最小算子,将该模糊多目标混合整数规划模型转化为求解等价的多个单目标混合整数线性规划问题;最后,采用两阶段算法求得问题的最优解.通过应用算例验证了模型的有效性和可行性.     

基于确定可能性均值法求解模糊随机双层规划问题

针对目标函数和约束函数中系数均为模糊随机变量的双层规划问题,基于模糊随机变量的期望值概念,将原模糊随机双层规划问题变形为一个模糊双层规划问题.采用模糊数的确定可能性均值对上下层目标函数进行去模糊化,利用基于可能性测度的模糊机会约束方法处理模糊约束函数,提出模糊随机双层确定可能性均值-机会约束规划模型,并给出其确定等价模型,再运用K次最好算法求解最终确定模型.最后通过数值例子验证了所提方法的可行性.     

电网规划中最小模糊缺负荷量计算方法

为在计及不确定性的电网规划中进行可靠性和经济性分析比较,提出了一种电网最小模糊缺负荷量计算方法．首先应用模糊集合论里的梯形模糊数描述电网规划中预测负荷及发电机可用率的不确定性,由此建立求解最小模糊缺负荷量的模糊线性规划模型,然后将其转化为参数线性规划模型,进而用推广的Ｂｌａｎｄ反转对偶单纯形算法进行求解．最后,给出了一个２４节点、３０条支路的算例．     

混合整数规划性质及其构造的超加性函数

针对混合整数规划的一般性案例,给出其对应的线性松弛规划表达.用3个具体案例来解读有效不等式在整数规划问题中的使用,引出Gomory整数割平面.构造超加性函数并探寻它和混合整数规划割平面的关系.分析结果表明:当超加性函数中的参数取值不同时,可以获得Gomory整数割平面、混合整数规划的取整割平面及混合整数规划的整数割平面.     

运输问题的区间规划模型

运输问题是运筹学中一类很重要的问题,但对于问题中有些参数很难给出精确值,因此,考虑采用不确定性规划描述此类问题,提出运输问题的区间规划模型,模型中用区间数来表示运输价格、产品供应量和需求量等难于确定的参数。根据参数实际的意义,针对所建立模型,利用区间规划的求解方法,将问题转化为确定型线性运输问题进行求解.最后给出一个算例,表明该算法的可行性。     

露天矿生产的车辆安排

分别基于两条原则对露天矿生产的车辆安排问题展开了讨论，建立了多目标非线性整数规划模型通过采用线性加权法、分离部分控制变量法，以及在一定范围内穷举，将问题简化，进而给出模型的求解方法不仅解决了具体实例中的问题，而且还给出了更为通用的一般模型及其优化的快速算法．     

Distribution Inventory Cost Optimization Under Grey and Fuzzy Uncertainty

0 IntroductionThe bullwhipeffect makes many parameters of supplychainbecome more uncertain[1].The customer demand andre-plenishment lead ti me are i mportant uncertain parameters insupply chaininventory system[2 ,3]. However , many researchesabout inventory control have made strong assumptions takingthe uncertain factors as stochastic[3-6]or deterministic parame-ters[2].These assumptions may make the models less realistic.The stochastic programming and fuzzy programming areusual uncertain pro…     

模糊环境下资金预算的机会约束NPV目标规划模型

运用净现值方法,考虑了当投资金额和回收期的现金流入与流出均为模糊变量,且投资者有多个目标时的资金预算问题,建立了资金预算的机会约束目标规划模型,并采用基于模糊模拟的遗传算法求解了模型问题.     

Fuzzy Economic Order Quantity Inventory Models Without Backordering

In economic order quantity models without backordering, both the stock cost of each unit quantity and the order cost of each cycle are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Based on an expected value criterion or a credibility criterion, a fuzzy expected value model and a fuzzy dependent chance programming (DCP) model are constructed. The purpose of the fuzzy expected value model is to find the optimal order quantity such that the fuzzy expected value of the total cost is minimal. The fuzzy DCP model is used to find the optimal order quantity for maximizing the credibility of an event such that the total cost in the planning periods does not exceed a certain budget level. Fuzzy simulations are designed to calculate the expected value of the fuzzy objective function and the credibility of each fuzzy event. A particle swarm optimization (PSO) algorithm based on a fuzzy simulation is designed, by integrating the fuzzy simulation and the PSO algorithm. Finally, a numerical example is given to illustrate the feasibility and validity of the proposed algorithm.     

带有模糊约束最短路问题的数学模型及算法

针对带有模糊约束的最短路问题,在其模糊线性规划模型的基础上,利用容差法和罚函数法对该模型进行转化,得到了与原模型具有相同最优解与最优值的转化模型,并提出一种修正的萤火虫算法求解转化模型.数值算例结果表明,该模型与算法对求解带有模糊约束的最短路问题有效.     

关联运输调度问题的模糊机会约束规划模型

提出了针对多车场多车型的关联运输调度问题(Multiple-depot and Heterogeneous-vehicle Incident Vehicle Routing Problem)的模糊机会约束规划模型,将问题模型中各个客户的需求量及各供货点库存看成是模糊参数,讨论了如何处理模糊目标函数,并讨论了改进的遗传算法和免疫克隆选择算法,比较其优劣。实验证明,对于求解该模型,免疫克隆选择算法能够快速收敛于全局最优解,优于改进的遗传算法,能有效地解决关联运输调度问题。     

Fuzzy Programming Models for Vendor Selection Problem in a Supply Chain

This paper characterizes quality, budget, and demand as fuzzy variables in a fuzzy vendor selection expected value model and a fuzzy vendor selection chance-constrained programming model, to maximize the total quality level. The two models have distinct advantages over existing methods for selecting vendors in fuzzy environments. A genetic algorithm based on fuzzy simulations is designed to solve these two models. Numerical examples show the effectiveness of the algorithm.     

Supply Chain Production-distribution Cost Optimization under Grey Fuzzy Uncertainty

Most supply chain programming problems are restricted to the deterministic situations or stochastic environments. Considering twofold uncertainty combining grey and fuzzy factors, this paper proposes a hybrid uncertain programming model to optimize the supply chain production-distribution cost. The programming parameters of the material suppliers, manufacturer, distribution centers, and the customers are integrated into the presented model. On the basis of the chance measure and the credibility of grey fuzzy variable, the grey fuzzy simulation methodology was proposed to generate input-output data for the uncertain functions. The designed neural network can expedite the simulation process after trained from the generated input-output data. The improved Particle Swarm Optimization (PSO) algorithm based on the Differential Evolution (DE) algorithm can optimize the uncertain programming problems. A numerical example was presented to highlight the significance of the uncertain model and the feasibility of the solution strategy.     

Supply China Production-distribution Cost Optimization under Grey Fuzzy Uncertainty

Most supply chain programming problems are restricted to the deterministic situations or stochastic environments. Considering twofold uncertainty combining grey and fuzzy factors, this paper proposes a hybrid uncertain programming model to optimize the supply chain production-distribution cost. The programming parameters of the material suppliers, manufacturer, distribution centers, and the customers are integrated into the presented model. On the basis of the chance measure and the credibility of grey fuzzy variable, the grey fuzzy simulation methodology was proposed to generate input-output data for the uncertain functions. The designed neural network can expedite the simulation process after trained from the generated input-output data. The improved Particle Swarm Optimization (PSO) algorithm based on the Differential Evolution (DE) algorithm can optimize the uncertain programming problems. A numerical example was presented to highlight the significance of the uncertain model and the feasibility of the solution strategy.     

FMS—AGV传输系统自学习调度方法

针对ＦＭＳ－ＡＧＶ传输系统调度的不确定性因素,对ＡＧＶ在线运行状态参数实时记录并学习,运用动态规划算法和模糊数学的方法,提出了模糊动态规划（ＦＤＰ）算法．给出了适于计算的迭代算式,结合人工智能（ＡＩ）编制了ＡＧＶ传输系统调度软件包．本算法利用在线记录的ＡＧＶ运行数据进行模糊处理和学习,有效地调节用于描述ＦＤＰ算法的模糊模型参数．这种自学习ＦＤＰ算法在ＡＧＶ的路径规划中有较好的适应性．对于一个新的ＦＭＳ－ＡＧＶ系统,经几次规划自学习之后,该算法就能很好地用于系统的实时调度中．     

伙伴挑选中的模糊可靠性优化模型

研究了伙伴挑选中的模糊可靠性优化问题,并设计了带有模糊约束和模糊目标的可靠性优化模型,利用隶属度定义将模糊优化模型进行清晰化处理·并设计了遗传算法进行了模型求解·大量实例计算表明了模型和算法的可行性和有效性