一种高压开关产品的装配过程优化问题研究

本文针对高压开关产品的装配线提出一个实际的装配过程优化问题:高压开关产品的装配过程优化问题。该问题是在传统的空间布局问题中,加入了装配线工艺流程约束,是一类新的优化问题。本文为该问题建立了整数规划模型,并为该模型开发了启发式算法。然后以ZF11-252产品的装配过程为例,采用启发式算法求解模型。     

基于Epsilon约束法的短纤维生产调度的双目标优化研究

针对短纤维生产行业实际,本文综合考虑客户的需求差异、客户的重要程度、纤维生产设备的准备时间以及交货期差异等因素,研究连续需求下的短纤维生产排序优化问题。首先,本文建立双目标整数规划模型,即最小化客户订单总延迟和最小化机器总准备时间;其次,设计Epsilon约束算法并调用CPLEX精确求解调度方案,即帕累托前沿;最后设计非支配排序的遗传算法(NSGA-II)求解大规模生产下的调度优化方案。通过实验,证明该整数规划模型和算法对解决多客户连续需求问题具有实际价值,进而可以为短纤维生产企业提供参考。     

混合整数规划求解多联票据印刷过程中的生产调度问题

多联票据的印刷过程包括排版、单联印刷和多联配页与装订三个过程。该过程是柔性的流水生产线与装配混合的生产系统。本文研究了该系统中的票据印刷生产调度问题,目标是最小化所有产品的最大完成时间（Makespan）。该问题到目前为止还没有人研究,本文首先建立了该问题的混合整数规划模型,然后提出了该模型的求解方法,并给出了该问题的下界。最后的量化示例和算例试验表明本文的模型是有效的。     

多态不确定环境下生产与运输方案的优化方法

研究了一类生产运输问题的优化模型,其中产地可供应量、机器可使用最大时间为模糊参数,市场需求和生产单位产品时间随机参数,在产地可供应量,市场需求,预算,产地机器可运转时间,目的地库存空间等约束下,该模型同时优化了生产运输的总成本和运输时间.基于修正后的S型曲线隶属函数和机会约束规划方法,推导了原模型的确定型等价式,并据此设计了寻求满意生产与运输方案的交互式算法。     

考虑订单合并和货物转运的多式联运路径优化研究

为了获得运输的规模经济效应,本文研究了一种考虑订单合并和货物转运的零担多式联运路径优化问题。首先,以总运输成本为目标函数,以网络中的运输工具容量、可以提供的运输工具最大数量、运输工具服务的关闭时间以及订单时间窗为约束,构建混合整数规划模型,在模型中允许多个订单进行合并运输并考虑运输过程中的转运成本。其次,由于多式联运路径优化问题是典型的NP-hard问题,为了快速求解该模型,开发了一种可以快速为该问题提供近似最优解和下界的列生成启发式算法。最后,生成并测试了大量算例,结果表明所开发的列生成启发式算法可以在较短的时间内提供高质量的近似最优解。文章所构建的模型和开发的列生成启发式算法可以为零担自营多式联运物流企业提供高效的决策支持。     

单件小批生产系统下模糊优化的动态随机投入产出模型

本文针对单件小批量生产系统 ,建立了模糊优化的动态随机投入产出模型 ,同时给出了该模型的递推解法 ,并用此模型对某单件小批企业在生产计划期的商品量进行了规划     

时变单车路径优化模型及动态规划算法

车辆路径问题由于其广泛的应用领域及经济价值而成为学术研究热点。然而,在已有的研究文献中,车辆的速度时变与服务多任务特性很少被关注。本文讨论了具有这两个特性的单车路径优化问题。建立了以送货完成时间最早为优化目标的时变单车送货路径优化模型。由于很难获得该模型的精确解,本文提出了一种贪婪补货策略压缩原问题解空间,设计动态规划算法给出了车辆行驶时间满足FIFO规则的送货顺序近似最优解。数值算例验证了该算法所得到的解仅是原问题的近似最优解这一结论。算例同时表明优化配送时间随着车辆装载能力的增大而缩短,并在车辆装载能力超过所有客户配送总需求时实现最短配送时间,即,使用较大装载能力车辆能节约更多配送时间。     

供应链多层规划问题及其合作对策协商求解

针对由制造商、分销中心和零售商组成的多级分布式供应链协同计划问题,建立了三层规划生产-分销计划谈判模型,设计了基于合作对策的两步协商方法。首先,基于模糊隶属度原理,将三层规划问题转化为单层规划问题。接着,设计了基于合作对策的两步协商过程,描述了两步协商模型和交互协商算法步骤,并对算法进行了性能分析。最后,给出了基于多层规划的协同生产-分销计划模型,并得到了基于合作对策的协商算法的解决方案。并通过与其它优化策略的对比,验证该解决方案的优越性。     

存在中间产品退出的混合型生产系统效率测度与分解研究

混合型生产系统是系统内部同时存在串联子系统和并联子系统的复杂生产系统.以存在中间产品退出的混合型生产系统为研究对象,针对其效率测度与分解问题在总系统效率函数表达、中间产品退出比例确定和子系统效率分解三方面的表征,构建了一种基于DEA理论框架的效率测度与分解模型.在求解该模型的过程中,借鉴交叉效率思想解决复杂模型非线性求解问题,并提出一种中立的第二目标规划优化效率分解中最优解不唯一问题.最后通过一个算例验证该模型的可行性和有效性.     

供应链中的多目标经济批量排产和运送问题的求解

当今供应链管理的目标已不再是只追求成本的最小化,越来越多的管理者和研究学者开始关注采用多个目标来对供应链的绩效进行优化.本文从一个供应商的角度出发,考虑了如何安排合理的生产排序来最小化生产周期和运送间隔以及最小化整条供应链中的单位时间的平均成本的批量排产和运送的问题.本文建立了该问题的多目标非线性混合整数规划模型,并提出了求解该问题的帕累托最优解集的方法.示例表明本文的算法是有效的.     

考虑交货期的生产运输联合优化问题研究

结合企业实际场景研究了考虑交货期的多个工厂、多条生产线、单一产品的生产与运输联合优化问题.已知客户订单需求量和交货时间窗,考虑了各条生产线在不同时段的生产能力约束,在满足交货时间窗约束的前提下,以生产、存储、运输费用之和极小化为目标建立了生产与运输联合优化问题的混合整数规划模型,通过分析模型结构证明了在不考虑固定生产成本的情况下,模型等价于最小费用最大流问题,得出了直接用Gurobi软件求解模型的可行性.最后利用具体算例进行模拟计算并与企业目前采用的顺序优化方法进行对比,发现采取联合优化策略可以明显降低总费用,并随着单位运输成本的增加,联合优化策略较顺序优化策略的优势在不断扩大.研究成果为企业制定生产与运输计划提供了理论依据.     

带时变生产成本的易变质经济批量模型的最优策略分析

考虑了具有时变生产成本的易变质产品经济批量模型．有限计划期内,单位生产成本、生产率以及需求率假定为时间的连续函数,生产固定成本则具有遗忘效应现象．当不允许缺货时,建立了以总成本最小为目标的混合整数优化模型并证明了此问题最优解的相关性质．对于此问题的特殊情形,将成本函数中的离散型变量松弛为连续型变量,通过分析其最优解的存在性及唯一性,求解了此最优解,将其作为初始值设计了求取一般情形最优解的有效算法．最后通过算例验证了理论结果的有效性．     

A multi-item mixture inventory model involving random lead time and demand with budget constraint and surprise function

This study deals with a multi-item mixture inventory model in which both demand and lead time are random. A budget constraint is also added to this model. The optimization problem with budget constraint is then transformed into a multi-objective optimization problem with the help of fuzzy chance-constrained programming technique and surprise function. In our studies, we relax the assumption about the demand, lead time and demand during lead time that follows a known distribution and then apply the minimax distribution free procedure to solve the problem. We develop an algorithm procedure to find the optimal order quantity and optimal value of the safety factor. Finally, the model is illustrated by a numerical example.     

On the flexibility of demand and production rate

In the manufacturing practice, cycle time is usually optimized in order to plan the batch size, and production time among other parameters. In certain situations, the production rate is decreased in order to have lower inventory levels or to deal with a shelf life constraint. This technical note examines the increase/decrease in the demand level along with a discussion concerning flexibility of the production rate. A generalized problem is also formulated in the context of the costs that are incurred in order to maintain certain demand level.     

Alternate risk measures for emergency medical service system design

The stochastic nature of emergency service requests and the unavailability of emergency vehicles when requested to serve demands are critical issues in constructing valid models representing real life emergency medical service (EMS) systems. We consider an EMS system design problem with stochastic demand and locate the emergency response facilities and vehicles in order to ensure target levels of coverage, which are quantified using risk measures on random unmet demand. The target service levels for each demand site and also for the entire service area are specified. In order to increase the possibility of representing a wider range of risk preferences we develop two types of stochastic optimization models involving alternate risk measures. The first type of the model includes integrated chance constraints (ICCs ), whereas the second type incorporates ICCs  and a stochastic dominance constraint. We develop solution methods for the proposed single-stage stochastic optimization problems and present extensive numerical results demonstrating their computational effectiveness.     

Fuzzy mixture two warehouse inventory model involving fuzzy random variable lead time demand and fuzzy total demand

This paper considers a two-warehouse fuzzy-stochastic mixture inventory model involving variable lead time with backorders fully backlogged. The model is considered for two cases—without and with budget constraint. Here, lead-time demand is considered as a fuzzy random variable and the total cost is obtained in the fuzzy sense. The total demand is again represented by a triangular fuzzy number and the fuzzy total cost is derived. By using the centroid method of defuzzification, the total cost is estimated. For the case with fuzzy-stochastic budget constraint, surprise function is used to convert the constrained problem to a corresponding unconstrained problem in pessimistic sense. The crisp optimization problem is solved using Generalized Reduced Gradient method. The optimal solutions for order quantity and lead time are found in both cases for the models with fuzzy-stochastic/stochastic lead time and the corresponding minimum value of the total cost in all cases are obtained. Numerical examples are provided to illustrate the models and results in both cases are compared.     

Optimal production inventory policy for defective items with fuzzy time period

In this paper, an optimal production inventory model with fuzzy time period and fuzzy inventory costs for defective items is formulated and solved under fuzzy space constraint. Here, the rate of production is assumed to be a function of time and considered as a control variable. Also the demand is linearly stock dependent. The defective rate is taken as random, the inventory holding cost and production cost are imprecise. The fuzzy parameters are converted to crisp ones using credibility measure theory. The different items have the different imprecise time periods and the minimization of cost for each item leads to a multi-objective optimization problem. The model is under the single management house and desired inventory level and product cost for each item are prescribed. The multi-objective problem is reduced to a single objective problem using Global Criteria Method (GCM) and solved with the help of Fuzzy Riemann Integral (FRI) method, Kuhn–Tucker condition and Generalised Reduced Gradient (GRG) technique. In optimum results including production functions and corresponding optimum costs for the different models are obtained and then are presented in tabular forms.     

Shipment planning at oil refineries using column generation and valid inequalities

In this paper we suggest an optimization model and a solution method for a shipment planning problem. This problem concerns the simultaneous planning of how to route a fleet of ships and the planning of which products to transport in these ships. The ships are used for moving products from oil refineries to storage depots. There are inventory levels to consider both at the refineries and at the depots. The inventory levels are affected by the process scheduling at the refineries and demand at the depots. The problem is formulated using an optimization model including an aggregated representation of the process scheduling at the refineries. Hence, we integrate the shipment planning and the process scheduling at the refineries. We suggest a solution method based on column generation, valid inequalities, and constraint branching. The solution method is tested on data provided by the Nynas oil refinery company and solutions are obtained within 4 hours, for problem instances of up to 3 refineries, 15 depots, and 4 products when considering a time horizon of 42 days.