炼钢连铸生产调度问题的两阶段遗传算法

将炼钢连铸生产过程抽象为混合流水车间,建立了0-1型混合整数线性规划调度模型。模型将严格连续浇注作为等式约束,并通过分段惩罚来平衡炉次的驻留时间。在对模型进行Benders分解的基础上,提出了将GA与LP结合的两阶段遗传算法。在算法设计中,提出了一种新的染色体编码来表示炉次设备指派与排序方案,给出了相应的遗传操作方法。算法的第一阶段通过最小化设备析取冲突来寻找高质量的种群,第二阶段通过求解线性规划模型来指导遗传算法的迭代过程。基于生产实际数据的仿真实验表明,该算法能够有效求解炼钢连铸生产调度问题。     

基于区间灰色区间数的多准则决策方法

将灰色模糊数扩展,定义了区间灰色区间数及其距离.针对准则值为区间灰色区间数的信息不完全的多准则决策问题,提出了一种基于目标规划法的灰色模糊多准则决策方法,求得最优权重向量,从而得到各方案的排序.最后给出一个算例说明方法的可行性和有效性.     

A hybrid genetic algorithm for train sequencing in the Korean railway

This article addresses the train-sequencing problem encountered in the Korean railway. It first presents a mixed integer programming model for the problem, in which the mileage must be balanced for each train route, while various field constraints must be satisfied, including overnight stay capacity and maintenance allocation restrictions. Then, it proposes a hybrid genetic algorithm as a solution approach to the problem. The proposed algorithm utilizes a modified elite group technique along with two heuristic procedures based on the mixed integer programming model. Finally, the proposed solution approach is tested with real-world data from the Korean railway. Numerical experiments under different conditions indicate that the proposed solution approach to the train-sequencing problem is promising.     

Manufacturing network configuration in supply chains with product recovery

Efficient implementation of product recovery requires appropriate network structures. In this paper, we study the network design problem of a firm that manufactures new products and remanufactures returned products in its facilities. We examine the capacity decisions and expected performance of two alternative manufacturing network configurations when demand and return flows are both uncertain.     

改进区间可接受度的证券投资组合区间二次规划模型

本文首先基于Markowitz的经典均值方差模型,针对不确定环境下的投资组合问题,把证券的收益率、风险损失率和流动性用区间数描述,建立了一种新的含交易成本的证券投资组合区间二次规划模型。其次,为求解该模型,提出了改进的区间可接受度确定性转换方法,通过引入优化水平α与可接受水平η将不确定二次规划转化为确定型规划。最后,通过数值实验将提出的方法与传统方法进行比较,结果表明本文所提出的方法与模型具有相对较好的可行性与实用性。     

Bi-objective multi-resource scheduling problem for emergency relief operations

Abstract

Resource scheduling for emergency relief operations is complex as it has many constraints. However, an effective allocation and sequencing of resources are crucial for the minimization of the completion times in emergency relief operations. Despite the importance of such decisions, only a few mathematical models of emergency relief operations have been studied. This article presents a bi-objective mixed integer programming (MIP) that helps to minimize both the total weighted time of completion of the demand points and the makespan of the total emergency relief operation. A two-phase method is developed to solve the bi-objective MIP problem. Additionally, a case study of hospital network in the Melbourne metropolitan area is used to evaluate the model. The results indicate that the model can successfully support the decisions required in the optimal resource scheduling of emergency relief operations.     

绿色增长下的导向性技术创新选择研究

针对如何正确引导 GHG 排放的气候反馈经济损失下导向性技术创新,以实现长期的绿色增长这一问题,基于 DICE 模型,重构导向性技术创新不同的动力要素及其与气候变化之间的内生关系,建立了可体现绿色增长“均衡性”、“包容性”和“可持续性”的非线性最优控制模型。数值仿真结果显示: 气候反馈经济损失不容小觑; 偏于生产的绿色技术创新导向下社会生产力强劲但存在气候环境恶化风险,偏于减排的绿色技术创新导向下气候反馈经济损失小但存在增长动力匮乏风险,二者虽均可实现长期的绿色增长,但中性的绿色技术创新导向会更稳妥; 偏于生产的绿色技术创新导向下人均消费变化率在短期内会显著提升。     

资产负债管理多阶段模型及应用

本文根据我国实际情况,考虑未来各种经济因素的不确定性,建立了资产负债管理问题多阶段随机优化模型.对基金公司的多阶段资产配置问题、个人财务计划问题、银行资产负债管理问题以及养老金问题进行研究,针对每一个具体问题对目标函数和约束条件进行了调整和改进.对未来不确定的经济因素采用向量自回归方法进行预测,得到了最优资产配置,使得与负债选择和投资者财富相联系的资产投资决策通过多期随机规划达到最优.     

基于混合DEA模型的医药行业上市公司经营效率相对有效性评价

DEA模型作为一种客观的多指标决策方法应用十分广泛.但目前使用频率较高的两种通用模型C²R模型和C²GS²模型,在单独使用时都有比较大的局限性,评判结果往往无法令人满意;针对这一问题,本文提出构建混合DEA模型,并应用混合DEA模型对医药上市公司的经营效率相对有效性评价进行实证分析,阐述了混合DEA模型的使用方法,验证了评判方法的可行性和科学性.     

动态联盟中伙伴选择问题的区间规划模型及其求解

伙伴选择和风险管理是动态联盟中的重要决策问题,当考虑失败风险时,失败概率无法给出精确值,因此,考虑采用不确定性规划描述此类问题.提出动态联盟中伙伴选择问题的区间规划模型,模型中用区间数表示联盟伙伴的失败概率.为了求解该模型,引入序关系,并利用Nakahara和Ishibuchi的定理,将区间规划模型转化为等价的清晰双目标模型.设计带自适应适值函数的遗传算法,求出问题的全部非劣解.经过对多个问题的仿真,证明了算法的有效性.