新形势下制造业物流体系布局优化研究

制造业物流体系是制造业与物流业协同发展衍生出的新体系模式。当前,我国已经迈入经济转型的攻关期。在这种新形势下,制造业物流发展面临着新的机遇。以沈阳市为例,探讨了物流体系布局优化的方法,并给出了布局优化模型。在阐述沈阳市制造业物流现状及存在问题的基础上,提出了沈阳市制造业物流体系布局优化方法及模型,旨为制造业物流体系的布局优化提供支持和应用参考。     

面向储能的光伏微网成本评价与对策研究

微电网是智能电网的重要组成部分,可以有效协调区域内的电力资源。为研究面向储能的光伏微网电力成本变化情况和优化对策,基于微网多主体结构构建微网电力成本均衡模型,以微网内分布式光伏供应及用户电力需求的统计数据为主要输入对象,并设置变量来区分不同情景下的分布式可再生能源发电量,建立以时间为自变量的微网分布式电力收益函数和用户购电成本函数,刻画微网电力资源调度的动态均衡变化。基于微网电力资源调度实例,发现微网在并网情景下的购电成本小于储能情景下的购电成本（C并=2 033.6元C储=2 633.6元）,且储能情景下购电成本的22.8%都来自储能设施的日折旧费,因此,加大科技研发和增强微网协同管理可以降低微网成本。     

关于优化齐齐哈尔历史文化资源的思考

历史文化资源是城市特有文化形态的依托和我体。能否挖掘、保护、梳理好历史文化资源，关系到城市优秀历史文化的继承与弘扬，关涉到城市未来的发展与走向。历史文化资源，不但要挖掘、整理、保护，更要优化。优化历史文化资源，就是在文明的大背景下，系统梳理历史文化资源，理清历史发展脉络，理清文明发展足迹，理清优秀历史文化传统，进而树立鲜明的城市文化形象，增强城市文化软实力。     

LC滤波器设计的优化解析公式

给出了改进的Chebyshev和Butterworth低通原型LC滤波器的解析设计公式.此公式充分利用阶数取整带来的余量,在不改变滤波器阶数的前提下减小了通带波动,极大地方便了集成滤波器的实现.给出了集成有源高通滤波器设计实例,验证了改进的Chebyshev和Butterworth低通原型LC滤波器解析设计公式的有效性.     

施工企业投标优化的问题与对策

通过对某大型施工企业多个铁路、公路施工项目部的调查，总结了企业当前投标优化方面存在的问题。针对企业以铁路、公路项目为主业的特点，提出了优势项目滚动发展、建立有效激励制度、做好投标准备、优化施工组织设计、应用报价技巧等优化对策。对于施工企业改善市场经营效果，提高中标质量，增加项目盈利有重要的借鉴作用。     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

Evaluation of multi-objective optimization approaches for solving green supply chain design problems

This paper evaluates the applicability of different multi-objective optimization methods for environmentally conscious supply chain design. We analyze a case study with three objectives: costs, CO₂ and fine dust (also known as PM – Particulate Matters) emissions. We approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods with pre-defined or adaptively selected parameters, two popular evolutionary algorithms, SPEA2 and NSGA-II, with different selection strategies, and their interactive counterparts that incorporate Decision Maker׳s (DM׳s) indirect preferences into the search process. Within this case study, the CO₂ emissions could be lowered significantly by accepting a marginal increase of costs over their global minimum. NSGA-II and SPEA2 enabled faster estimation of the Pareto front, but produced significantly worse solutions than the exact optimization methods. The interactive methods outperformed their a posteriori counterparts, and could discover solutions corresponding better to the DM preferences. In addition, by adjusting appropriately the elicitation interval and starting generation of the elicitation, the number of pairwise comparisons needed by the interactive evolutionary methods to construct a satisfactory solution could be decreased.     

Optimal determination of the parameters of some biased estimators using genetic algorithm

In this paper, some new algorithms for estimating the biasing parameters of the ridge, Liu and two-parameter estimators are introduced with the help of genetic algorithm (GA). The proposed algorithms are based on minimizing some statistical measures such as mean square error (MSE), mean absolute error (MAE) and mean absolute prediction error (MAPE). At the same time, the new algorithms allow one to keep the condition number and variance inflation factors to be less than or equal to ten by means of the GA. A numerical example is presented to show the utility of the new algorithms. In addition, an extensive Monte Carlo experiment is conducted. The numerical findings prove that the proposed algorithms enable to eliminate the problem of multicollinearity and minimize the MSE, MAE and MAPE.     

中国—东盟政治合作机制研究

本文根据中国—东盟区域合作发展的政治合作机制的概念及呈现的多维特性,运用政治合作的目标分解和构成要素,对政治合作机制进行综合的结构分析。通过利益泛化(低度)、制度分化(中度)和价值固化(深度)生成的三个阶段性使命目标(和睦共享、和平共处与和谐共荣)合作过程的剖析,对中国—东盟政治合作机制建设的结构性问题进行探讨,以此助推区域政治合作机制的改进和优化。     

考虑储存成本的集装箱公铁联运路径优化

联运企业的效益受运输路径和运输方式的影响。如何降低联运成本、提高联运企业的效益,已成为学术研究的重中之重。针对集装箱公铁联运路径优化问题,以运输成本、换装成本、储存成本、时间惩罚成本构成的运输总成本为目标函数,建立集装箱公铁联运路径优化模型,考虑运输时间限制、班期限制、节点储存成本,得出使运输总成本最低的运输路径及运输方式,并利用算例验证模型的有效性。