Evacuation planning using multiobjective evolutionary optimization approach

In an emergency situation, evacuation is conducted in order to displace people from a dangerous place to a safer place, and it usually needs to be done in a hurry. It is necessary to prepare evacuation plans in order to have a good response in an emergency situation. A central challenge in developing an evacuation plan is in determining the distribution of evacuees into the safe areas, that is, deciding where and from which road each evacuee should go. To achieve this aim, several objective functions should be brought into consideration and need to be satisfied simultaneously, though these objective functions may often conflict with each other.     

Supplier default dependencies: Empirical evidence from the automotive industry

Common ways to mitigate the detrimental consequences of supplier bankruptcies are to install redundancy and to pursue a multiple-sourcing strategy. This is based on the assumption that the adverse event of one supplier going out of business is largely independent from the default of other suppliers. However, this implicit assumption does not hold in all cases. This study – based on empirical data from automotive suppliers – reveals that default dependencies among suppliers do often exist and can have significant consequences. We use copula functions, a method of representing joint distribution functions with particular marginals, to capture the default dependence between automotive suppliers and to simulate various default dependence scenarios. We also conduct a comparative static analysis illustrating the significant impact of default correlation in a supplier portfolio. Our findings should spur managers to analyze their supplier portfolios with respect to default dependencies, and to take this phenomenon into consideration when making sourcing decisions.     

Distributed supply chain management using ant colony optimization

Successful supply chain management requires a cooperative integration between all the partners in the network. At the operational level, the partners individual behavior should be optimal and therefore their activities have to be planned using sophisticated optimization tools. However, these tools should take into account the planning of the remaining partners, through the exchange of information, in order to allow some kind of cooperation between the elements of the chain. This paper introduces a new supply chain management technique, based on modeling a generic supply chain with suppliers, logistics and distributers, as a distributed optimization problem. The different operational activities are solved by the optimization meta-heuristic called ant colony optimization, which allows the exchange of information between different optimization problems by means of a pheromone matrix. The simulation results show that the new methodology is more efficient than a simple decentralized methodology for different instances of a supply chain.     

Channel coordination through a revenue sharing contract in a two-period newsboy problem

This paper studies channel coordination through revenue sharing contract between a single retailer and a single wholesaler in a two-period newsboy problem. Two models are discussed, a single-buying-opportunity model and a two-buying-opportunity model. We discuss how the revenue sharing ratio and the wholesale prices are to be determined in order to achieve channel coordination and a win–win outcome. We find that the wholesale prices are set to be lower than the retail prices and the optimal revenue sharing ratio is linearly increasing in the wholesale prices. The proposed revenue sharing contract has more flexibility than price protection, in that the optimal revenue sharing ratio can be settled reasonably through negotiation between the retailer and wholesaler.     

A reference model for customer-centric data mining with support vector machines

Supervised classification is an important part of corporate data mining to support decision making in customer-centric planning tasks. The paper proposes a hierarchical reference model for support vector machine based classification within this discipline. The approach balances the conflicting goals of transparent yet accurate models and compares favourably to alternative classifiers in a large-scale empirical evaluation in real-world customer relationship management applications. Recent advances in support vector machine oriented research are incorporated to approach feature, instance and model selection in a unified framework.     

Studying the interdependence of contractual and operational flexibilities in the market of specialty chemicals

This paper focuses on the market of specialty chemicals and deals with the joint investigation and valuation of contractual and operational flexibilities from a manufacturers’ point of view. In this market, customized services related to research, development and manufacturing of chemicals, intermediates and active pharmaceutical ingredients are offered to a small number of customers. Traditionally, customers are granted a large degree of freedom with respect to demand quantity and time exposing the manufacturer to high uncertainty and financial risk. Using a model-based approach we quantify the effect of this contractual flexibility and relate it to the manufacturing flexibility concerning capacity allocation. Through the valuation of these flexibilities we provide first insights for the manufacturer on which customer requests to accept, how to set up the associated contracts with the customers and how to allocate capacity for a given portfolio of products.     

高职院校企业化课堂管理的效果评价——以有机化学课为例

随着职业教育的快速发展,高职院校转型发展势在必行。将企业化管理模式应用到高职院校的课堂管理中,通过观念转变、角色转变、制度转变对此管理模式进行了分析;并以有机化学课为例,运用模糊层次分析法对其管理效果进行客观、科学地评价。结果表明企业化课堂管理模式能较好地适应高职院校转型发展的需要,对其教学改革具有一定的参考价值。     

SDN框架下不良数据计算机网络管理系统设计

近年来,随着互联网的飞速发展,网络信息交互量不断增大。各类不良网络交互信息数据充斥着网络交互空间,给网络社交秩序造成破坏。为此,一系列网络不良数据管理系统孕育而出。通过长期实践发现,传统不良数据计算机网络管理系统的管理方式存在不良数据动态检测性不强、不良信息数据内容识别度低、不良数据管理逻辑性差等问题。通过与SDN框架的优势相结合,提出SDN框架下不良数据计算机网络管理系统设计。采用NVR数据量交互模块、数据特征DNA内容识别算法与大数据统筹规划模块,对传统不良数据管理系统方式中存在的问题进行解决。通过实验证明,提出的SDN框架下不良数据计算机网络管理系统比传统的数据管理系统,在不良数据识别、检测、统计、管理等方面上具有绝对优势。     

用于高压电能表的新型电源管理单元设计

新型高压电能表具有计量精度高、低功耗、信息化、智能化等优点,获得了越来越多的应用。论文对新型电能表计量装置的供电需求进行了探讨,在此基础上设计了一基于感应电流取能的新型电源管理单元,在稳压器输入端增加了电能智能存储功能,确保在极端工作条件下,电能表仍具有计量、数据存储、无线抄收等功能,避免了因利用该技术出现断电及断电重启时刻导致的计量损失。测试结果表明,电源管理单元能够确保电能表在极端情况下稳定工作4.5小时。