物料管理中投料批量和订货批量的决策

通过分析不同种类物料的加工及采购特性,针对物料投料提出一种平衡的优化投料批量决策技术,降低总的加工成本;针对物料采购提出一种订货批量决策技术,合理的降低库存.实验结果表明,该算法简明,便于操作,具有实用价值.     

信号灯控制的多阶段决策模型及其前向动态规划算法

为研究路口交通信号灯的实时最优控制问题,提出一种以最小化等待时间为目标的多阶段决策模型.该模型利用最短绿灯和红灯时间的结构特征,通过合理选择系统状态和控制变量压缩了模型规模,进而提出了前向动态规划算法以高效得到最优解.数值实验显示,对比于固定时长的周期性控制可以节省路口车辆的等待时间;对比基于混合整数规划的求解方法,可以提高求解效率,满足实时控制的要求.     

Integrated inventory control and inspection policies with deterministic demand

In this paper, we develop integrated inventory inspection models with and without replacement of nonconforming items. Inspection policies include no inspection, sampling inspection, and 100% inspection. We consider a buyer who places an order from a supplier. When a lot is received, the buyer uses some type of inspection policy. The fraction nonconforming is assumed to be a random variable following a beta distribution. Both the order quantity and the inspection policy are decision variables. In the inspection policy involving determining sampling plan parameters, constraints on the buyer and manufacturer risks are set in order to obtain a fair plan for both parties. A solution procedure for determining the operating policies for inventory and inspection consisting of order quantity, sample size, and acceptance number is proposed. Numerical examples are presented to conduct a sensitivity analysis for important model parameters and to illustrate important issues about the developed models.     

Optimal order policy in response to announced price increase for deteriorating items with limited special order quantity

When a supplier announces an impending price increase due to take effect at a certain time in the future, it is important for each retailer to decide whether to purchase additional stock to take advantage of the present lower price. This study explores the possible effects of price increases on a retailer's replenishment policy when the special order quantity is limited and the rate of deterioration of the goods is assumed to be constant. The two situations discussed in this study are as follows: (1) when the special order time coincides with the retailer's replenishment time and (2) when the special order time occurs during the retailer's sales period. By analysing the total cost savings between special and regular orders during the depletion time of the special order quantity, the optimal order policy for each situation can be determined. We provide several numerical examples to illustrate the theories in practice. Additionally, we conduct a sensitivity analysis on the optimal solution with respect to the main parameters.     

A supplier selection and order allocation problem with stochastic demands

We consider a system comprising a retailer and a set of candidate suppliers that operates within a finite planning horizon of multiple periods. The retailer replenishes its inventory from the suppliers and satisfies stochastic customer demands. At the beginning of each period, the retailer makes decisions on the replenishment quantity, supplier selection and order allocation among the selected suppliers. An optimisation problem is formulated to minimise the total expected system cost, which includes an outer level stochastic dynamic program for the optimal replenishment quantity and an inner level integer program for supplier selection and order allocation with a given replenishment quantity. For the inner level subproblem, we develop a polynomial algorithm to obtain optimal decisions. For the outer level subproblem, we propose an efficient heuristic for the system with integer-valued inventory, based on the structural properties of the system with real-valued inventory. We investigate the efficiency of the proposed solution approach, as well as the impact of parameters on the optimal replenishment decision with numerical experiments.     

一种求解整数规划与混合整数规划非线性罚函数方法

证明了任何一个变量有界的整数规划问题（IP）和混合整数规划问题（MIP）都可以转化为一个等价的非整数（或连续化）规划问题（NIP）,并给出一个用非线性精确罚函数法来求解该等价NIP的方法,从而达到求解IP或MIP的目的,数值实验表明了算法的可行性。该方法可广泛用于各应用领域里IP和MIP的求解,特别是为非线性IP和MIP问题提供了一条通用 的求解途径,对解决许多实际优化问题具有重要意义。     

用于炼油厂原油库存调度的混合模拟退火算法

现有的数学规划法在解决原油库存调度优化问题时存在着组合爆炸的问题,是阻碍调度优化实用化的主要原因。由于实践中往往只要求快速地获得一个较好解,因此作为启发式算法之一的模拟退火法,在解决调度问题的实用化方面具有很大的优越性。但由于模拟退火法较适于处理无约束的整数规划问题,而在原油库存调度优化模型中却存在着大量的实数约束,所以在其中直接应用模拟退火法比较困难。该文将模拟退火法与线性规划法相结合,以前者调动后者,后者为前者提供可行解判据,构成了一种优化混合算法。在将混合算法应用于原油库存调度问题时,该文采用了特定的编码方式,使各控制变量在随机变化时尽量满足相关的约束条件,从而避免了许多无效解的产生。实例计算结果表明,同传统的混合整数线性规划方法相比,这种混合算法可以快速地给出优化解,其优化值与全局最优值差别不大,表明混合算法可以更好地解决实际原油调度问题。     

钢厂合同计划的模型与算法

通过对钢厂生产过程的分析,建立了合同计划编制的整数规划模型,并提出用基于可重复自然数编码和三变异算子的遗传算法对模型进行求解。以热轧厂合同计划编制为例进行实验,结果表明,此模型符合生产实际,获得的结果优于人机交互系统,求解算法比较有效。     

模糊控制理论在库存货位管理中的应用

针对库存货位布局线性规划的难建模和全重排问题,提出了基于模糊控制理论的库存货位布局方法。在以某公司仓库的实际数据平台基础上,通过选取隶属度函数,建立模糊规则库,进行模糊推理和判决解决了线性规划中存在的问题。重点讨论了模糊控制方法的具体实现步骤。     

Solving lot-sizing problem with quantity discount and transportation cost

Owing to today's increasingly competitive market and ever-changing manufacturing environment, the inventory problem is becoming more complicated to solve. The incorporation of heuristics methods has become a new trend to tackle the complex problem in the past decade. This article considers a lot-sizing problem, and the objective is to minimise total costs, where the costs include ordering, holding, purchase and transportation costs, under the requirement that no inventory shortage is allowed in the system. We first formulate the lot-sizing problem as a mixed integer programming (MIP) model. Next, an efficient genetic algorithm (GA) model is constructed for solving large-scale lot-sizing problems. An illustrative example with two cases in a touch panel manufacturer is used to illustrate the practicality of these models, and a sensitivity analysis is applied to understand the impact of the changes in parameters to the outcomes. The results demonstrate that both the MIP model and the GA model are effective and relatively accurate tools for determining the replenishment for touch panel manufacturing for multi-periods with quantity discount and batch transportation. The contributions of this article are to construct an MIP model to obtain an optimal solution when the problem is not too complicated itself and to present a GA model to find a near-optimal solution efficiently when the problem is complicated.     

基于混合逻辑动态模型的混杂系统预测控制

针对过程工业控制对象的混杂特性,采用基于混合逻辑动态模型的预测控制策略。给出混杂系统的建模方法,并对其稳定性进行分析。仿真结果表明基于混合逻辑动态模型的预测控制能使混杂系统跟踪设定值并满足操作约束,为研究新一代复杂工业控制系统提供了新的思路。     

基于随机模型预测控制的含大规模风电接入的电力系统优化调度

风电是重要的清洁可再生能源,将其引入智能电网中对节能减排有着重要的意义.为降低大规模风电不确定性给电网调度带来的影响,提出一种基于随机模型预测控制的风电与传统机组协调调度方法.考虑了部分传统机组需要人工调度而无法频繁、连续操作的情况,并引入可调负荷以增加系统可调度能力.构建基于混合整数二次规划(MIQP)的风电调度目标函数,以及包括机组最大可调节次数、最小运行/停机时间、可调度负荷总能量需求一致性、风电切负荷比例等约束.提出两阶段场景缩减方法以实现典型场景的快速筛选.通过与传统开环调度方法的性能对比表明所提出方法的可行性与有效性,并在此基础上进一步分析机组启停次数和可调度负荷对系统运行的影响.     

一类混杂系统的模型预测控制

采用基于混合逻辑动态的建模方法,将系统的连续动态过程、逻辑部分和操作约束表示为带有混合整数不等式约束的线性状态方程的形式．给出了混杂系统的建模原理,并采用预测控制策略对系统进行控制．具体实例的仿真结果表明基于混合逻辑动态模型的预测控制能使混杂系统跟踪设定值并满足操作约束．     

一类混杂系统建模和优化控制的研究

为解决混杂系统优化控制的计算复杂性问题,针对结合逻辑规则的工业过程混杂模型,采用结合约束程序的混合整数非线性规划算法,求解这种混杂模型的优化控制。计算实例表明,通过混杂建模方法,可以充分利用工业对象的机理模型以及操作工经验或专家经验,建立系统的更精确模型;结合约束程序混合整数非线性规划算法可以较迅速地求解混杂模型优化控制问题,从而使该方法可以用于工业过程实时控制中。     

供应链牛鞭效应的随机控制

牛鞭效应是一个衡量供应链管理运作是否良好的重要指标参数．本文采用随机控制理论方法,针对在文[1]基础上建立的具有多分销中心的供应链动态库存模型,以供应链系统中的订货作为控制变量抑制牛鞭效应．同时以一个石油分销系统为对象进行了供应链牛鞭效应的随机控制仿真实验,实验表明牛鞭效应受到了抑制．