具有非对称模糊加工时间工期指派调度优化问题的一类加权模型及其求解算法

根据模糊变量截集所表达的信息的重要程度,建立了模糊环境下工期指派调度优化问题的一类加权模型,该模型中工件加工时间为非对称三角模糊数,目标函数为极小化提前完工惩罚和拖期完工惩罚和的加权可能性均值.证明了当工件加工时间具有相同宽度比时,模型是多项式可解的,并给出了求解的多项式算法.数值实验表明加权模型与现有的非加权模型相比能有效的降低总费用.     

模糊环境下带交易费用的权证定价模型——纪念李国平院士吴新谋教授诞辰100周年

该文综合考虑我国证券市场中广泛存在的隐性交易费用, 建立了模糊环境下带交易费用的权证定价模型. 在假设交易费用率为三角型模糊数的前提下导出了新的权证价格区间, 并通过引入模糊期望的概念, 将区间数转化为与投资者主观判断无关的准确数. 基于此模型, 对模型中三角型模糊数的关键参数 进行了灵敏度分析和投资策略分析.     

模糊环境下批量制造业提前/拖期交货的生产计划

描述了基于客户需求为模糊量的批量生产提前/拖期交货的生产计划,并建立了模糊环境下的三个模型.为了有效求解优化模型,我们将模糊模拟和遗传算法相结合给出了混合智能算法.最后通过数值例子说明算法的有效性.     

模糊环境中跳扩散模型下带交易费用的期权定价方法

不确定性是金融市场的一大特性,许多金融数据不能用确定的数来表示,例如人们经常运用市场无风险利率为5%左右,波动率3%左右等等这些具有模糊性的数据,为了描述这些数据,模糊数学被引入到金融理论中.该文将在标的资产服从Merton跳扩散过程的基础上,考虑模糊环境中带有交易费用的期权定价问题.首先,推导出跳扩散模型下带有交易费用的欧式看涨期权的定价公式.然后,将模糊理论引入到期权定价中,得到模糊环境中跳扩散模型下带交易费用的期权定价公式,再利用模糊积分进行退模糊化.最后,运用Sage软件对模型进行数值分析,并与已有模型进行比较.     

模糊环境下可控提前期供应链库存优化的Stackelberg模型研究

为了有效地缩短提前期与降低库存成本,研究了模糊环境下可控提前期的供应链库存优化问题.利用三角形模糊数描述需求的不确定性,建立了一类模糊需求条件下可控提前期供应链库存优化的Stackelberg模型.利用三角形模糊数描述成本系数的不确定性,建立了模糊成本系数条件下可控提前期供应链库存优化的Stackelberg模型,并提出利用均值面积度量法来解模糊化.通过数值分析来验证两类模型的优化效果.     

模糊环境下资金预算的期望净现值模型

资金预算问题是指对一项投资机会是否应该付诸实施进行判断.净现值方法(NPV)一直是现代资本预算方法的传统核心内容.将传统的净现值方法扩展到模糊环境下,讨论了当现金流入和现金流出为模糊变量情况下,如何选择最优的项目.建立了模糊环境下的均值NPV模型,并设计了基于模糊模拟的遗传算法,给出了模型问题的一般解决方法.     

不确定条件下工程项目的多目标模糊均衡优化

在工程项目多目标优化问题研究基础上,研究不确定环境下工程项目多目标均衡优化问题.利用模糊数表示费用变化率和质量变化率,考虑模糊集的不同可能性水平,建立工程项目多目标模糊均衡优化模型,给出模型的求解方法和步骤,得到不同可能性水平下多目标优化问题的最优折衷解变化范围.优化方法使决策者能够根据决策风险的大小进行最优目标值的确定.     

基于最小交易量和交易费用的多阶段模糊投资组合

考虑了在摩擦市场下的多阶段模糊投资组合模型,基于半绝对方差风险函数,建立了带有最小交易量和交易费用限制的收益最大化多阶段模糊投资组合模型.利用绝对值函数的性质,将模型转化为混合整数线性规划形式,并通过实例验证了模型的可行性,最后对模型与基于可能性均值和可能性方差的多阶段模糊投资组合模型进行了对比,分析了模型的优越性,并验证了模型的可行性.     

模糊环境下带交易费用的权证定价模型

该文综合考虑我国证券市场中广泛存在的隐性交易费用,建立了模糊环境下带交易费用的权证定价模型.在假设交易费用率为三角型模糊数的前提下导出了新的权证价格区间,并通过引入模糊期望的概念,将区间数转化为与投资者主观判断无关的准确数.基于此模型,对模型中三角型模糊数的关键参数进行了灵敏度分析和投资策略分析.     

模糊随机环境下的企业综合实力评价模型研究

建立随机环境下的定量指标评价模型、模糊随机环境下的定性指标评价模型和权重为模糊变量的综合评价模型,研究定量评价指标、定性评价指标分别为随机变量和模糊随机变量的企业综合实力评价模型和评价分析方法.最后,以制造业中HX行业的CA企业为例,实证模拟验证了模型的有效性和可操作性.     

A mixed integer programming model for advanced planning and scheduling (APS)

This paper presents a mixed integer programming (MIP) model which succeeds in a system integration of the production planning and shop floor scheduling problems. The proposed advanced planning and scheduling (APS) model explicitly considers capacity constraints, operation sequences, lead times and due dates in a multi-order environment. The objective of the model is to seek the minimum cost of both production idle time and tardiness or earliness penalty of an order. The output of the model is operation schedules with order starting time and finish time. Numerical result shows that the suggested APS model can favorably produce optimal schedules.     

A robust optimization model for multi-site production planning problem in an uncertain environment

This paper addresses the multi-site production planning problem for a multinational lingerie company in Hong Kong subject to production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers’ preferences, as well as production capacity, workforce level, storage space and resource conditions at the factories. In this paper, a robust optimization model is developed to solve multi-site production planning problem with uncertainty data, in which the total costs consisting of production cost, labor cost, inventory cost, and workforce changing cost are minimized. By adjusting penalty parameters, production management can determine an optimal medium-term production strategy including the production loading plan and workforce level while considering different economic growth scenarios. The robustness and effectiveness of the developed model are demonstrated by numerical results. The trade-off between solution robustness and model robustness is also analyzed.     

考虑模糊时间和成熟度的跨区域鲜果电商配送模型研究

基于现实配送过程中配送时间存在着不确定性,通过配送时间模糊化处理构建出跨区域鲜果电商配送模糊网络流模型,进而根据实际配送时间与期望配送时间的偏离建立顾客满意度函数,然后构建由满意度降低引起的惩罚成本函数,并根据鲜果成熟度变化特性建立带有模糊时间和成熟度的跨区域鲜果电商配送最小成本路线优化模型。在求解过程中利用三种去模糊化方法(重心法、积分法和α-cut法)对模糊时间进行处理,并结合现有的整数规划算法对模型进行求解,得出最佳配送路线并进行对比分析。结果表明:(1)根据鲜果成熟度水平选择适当的配送路线可以有效降低配送成本,保证鲜果品质;(2)在去模糊化方面α-cut法比重心法和积分法所得结果更具有一般性。     

A Crop Planning Problem with Fuzzy Random Profit Coefficients

The main purpose of this paper is to present a crop planning problem for agricultural management under uncertainty. It is significant that agricultural managers assign their limited farmlands to cultivation of which crops in a season. This planning is called the crop planning problem and influences their incomes for the season. Usually, the crop planning problem is formulated as a linear programming problem. But there are many uncertain factors in agricultural problems, so future profits for crops are not certain values. A linear programming model with constant profit coefficients may not reflect the environment of decision making properly. Therefore, we propose a model of crop planning with fuzzy profit coefficients, and an effective solution procedure for the model. Furthermore, we extend this fuzzy model, setting the profit coefficients as discrete randomized fuzzy numbers. We show concrete optimal solutions for each models.     

Fuzzy programming and profit and cost allocation for a production and transportation problem

In this paper, we deal with a real problem on production and transportation in a housing material manufacturer, and consider a production and transportation planning under the assumption that the manufacturer makes multiple products at factories in multiple regions and the products are in demand in each of the regions. First, we formulate mixed zero–one programming problems such that the cost of production and transportation is minimized subject to capacities of factories and demands of regions. Second, to realize stable production and satisfactory supply of the products in fuzzy environments, fuzzy programming for the production and transportation problem is incorporated. Finally, under the optimal planning of production and transportation, we show a profit and cost allocation by applying a solution concept from game theory. Using actual data, we show usefulness of the fuzzy programming and a rational allocation scheme of the profit and cost.     

基于可信性理论的生产计划期望值模型

基于可信性理论,提出一类新的模糊生产计划期望值模型.然后,讨论这个模糊生产计划模型的基本性质.最后,利用这个模糊模型的基本性质我们可以把模糊生产计划期望值模型转化为一个线性规划模型并且设计相应的算法求解模糊生产计划问题的一个数值例子.     

基于模糊遗传算法的自融资有效投资组合研究

在马克维茨投资组合的均值一方差模型框架下,给出限制投资数量的自融资投资组合优化模型.把预期收益率不等式约束转化为模糊约束,采用一种通过惩罚因子,对适应度函数进行修正的模糊遗传算法来求解模型.在理论上,这种算法能够将最优基因较完整地遗传到下一代,有效地避免了早熟现象,可以得到更好的适应度函数值.在实际应用中,对一具体自融资有效投资组合实例进行计算,结果表明:本文所提出的模糊遗传算法是可行的、有效的,具有更好的优化结果.     

In–Out Algorithm for assortment planning under a ranking-based consumer choice model

We consider a retailer’s assortment planning problem under a ranking-based consumer choice model. The retailer incurs a fixed carrying cost per product offered, a substitution penalty cost for each customer who does not purchase his first choice, and a penalty cost on lost sales. We develop an effective In–Out Algorithm to identify the optimal solution. The extensive numerical study shows that the algorithm performs well, and is more than 10,000 times faster than enumeration on problems with 20 products.     

A robust optimization model for a cross-border logistics problem with fleet composition in an uncertain environment

Since the implementation of the open-door policy in China, many Hong Kong-based manufacturers' production lines have moved to China to take advantage of the lower production cost, lower wages, and lower rental costs, and thus, the finished products must be transported from China to Hong Kong. It has been discovered that logistics management often encounters uncertainty and noisy data. In this paper, a robust optimization model is proposed to solve a cross-border logistics problem in an environment of uncertainty. By adjusting penalty parameters, decision-makers can determine an optimal long-term transportation strategy, including the optimal delivery routes and the optimal vehicle fleet composition to minimize total expenditure under different economic growth scenarios. We demonstrate the robustness and effectiveness of our model using the example of a Hong Kong-based manufacturing company. The analysis of the trade-off between model robustness and solution robustness is also presented.     

模糊随机需求的连续盘点存储策略研究

考虑到需求的模糊随机性,建立模糊随机需求情况下连续盘点存储策略的模糊随机成本模型。利用模糊随机变量的期望值理论,推导出了其成本期望值模型的解析表达式,进而给出了最优再订货点所属区间的判别条件以及最优再订货点和经济订货量的计算式;基于此,设计了一模糊随机需求的连续盘点最优存储策略算法。最后结合数值算例,分析了模糊随机需求概率分布及缺货成本对最优存储策略的影响。