Improving supplier performance using a comprehensive scheme

Improving and coordinating buyer and supplier efforts to increase productivity and competitive advantage in a supply chain is an important issue. Numerous studies have proposed models, principles and criteria for supplier evaluation and selection. Hence, evaluating and improving supplier performance are important when building long-term supply chain competitiveness. This study presents a novel and comprehensive framework that illustrates the linkages between evaluating supplier performance and planning improvements. The proposed framework comprises four parts: building an evaluation model, evaluating supplier performance based on the buyer perspective, evaluating supplier performance based on the supplier perspective and scheduling improvement tasks. This study applies a hybrid genetic algorithm to help suppliers schedule improvement tasks based on the evaluation findings. Finally, evaluation data of a light-emitting diode (LED) manufacturer in Taiwan is used to interpret the procedure and verify model effectiveness.     

Talking About Genetics: Community Perceptions of the Importance of Biological Inheritance for Determining Child Outcome

As part of a study of community attitudes toward adoption, 82 Canadians responded to questions concerning the importance of biological inheritance for determining child outcome, whether it is important for a person to know a great deal about his or her biological background, and what particular things a person should know about his or her biological background. Substantial support existed for the need to know one's biological background, especially medical history. Reference to scientific studies, genes, and genetics were strongly associated with “very important” responses; but parenting and sociocultural family environment were viewed as mediating the influence of biological inheritance. Implications for adoption practice are considered.     

基于二元产权的共同治理机制研究

二元产权制度安排通过对人力资本要素价值创造潜力的挖掘和释放驱动企业价值高效增长,是知识经济时代理想的产权制度安排。传统公司治理机制不适应于二元产权制度,二元产权制度下的三源价值影响力场决定,治理模式必须由股东单边治理转向要素资本所有者共同治理。共同治理模式蕴含共同决策机制、共同制衡机制、激励引导机制和社会治理补充机制。在这一治理模式下,人力资本投资者、物力资本投资者和债务资本投资者以产权保护为核心目的,通过对决策、制衡、监督和约束等环节的深度参与,从根本上改善了公司治理环境、提高了公司治理效率,成为驱动企业价值的重要制度资源。     

最小时间窗规则及其在混合遗传算法中的应用

为了研究与优先规则结合的混合遗传算法,提出了最小时间窗规则(STW),设计了采用最小时间窗规则生成初始种群的算法.发现调度结果中时间窗越少和越小,则完工时间就越小.探讨了优先规则应用于遗传算法中在生成初始种群时的完工时间、广义海明距离和完工时间的标准偏差等性能指标.对不同规模基准调度问题的测试结果表明,STW规则在以最小化完工时间为目标的调度中,与其他几种简单规则相比,能产生较好的调度效果.在混合遗传算法中,采用STW规则产生的初始种群整体适应度最高,多样性较好.     

基于模拟退火遗传算法(N+M)容错系统优化模型的求解

本文提出了求解（N＋M）容错系统优化模型的模拟退火遗传算法．该算法在遗传算法的约束条件处理、交叉和变异概率选取、变异个体等环节引入了模拟退火机制，实现了模拟退火和遗传算法的融合，进一步改善算法的搜索能力、搜索效乍和收敛性能，计算结果验证了算法的有效性和正确性。     

非线性动态液位软测量

文章设计了一种具有高度非线性逼近能力的人工神经网络模型结构,以遗传算法进行该模型参数的组合优化建模,解决连续搅拌反应釜动态液位测量问题。     

基因专利保护问题研究 ——基因资源提供者参与分享基因专利利益探讨

尽管在基因的可专利性问题上仍存有争议,但各国的立法和司法实践已经做出了 带有明显倾向性的举动。然而,在基因资源提供者参与分享基因专利利益方面却没有那么幸 运,在分享的法哲学基础、法律上的可操作性以及分享的具体模式方面还有大量工作要做。 文章对上述问题进行了详细地分析和探讨。     

多波长后向泵浦拉曼放大器优化算法研究

介绍了多波长后向泵浦拉曼放大器的原理和数学分析方法,设计了一种有效的泵浦优化算法,该算法包括改进的遗传算法和打靶法。数值仿真得到了带宽为80 nm、平均开关增益为5.93 dB的拉曼放大,其增益起伏小于1 dB。     

Node deletion sequences in influence diagrams using genetic algorithms

Influence diagrams are powerful tools for representing and solving complex inference and decision-making problems under uncertainty. They are directed acyclic graphs with nodes and arcs that have a precise meaning. The algorithm for evaluating an influence diagram deletes nodes from the graph in a particular order given by the position of each node and its arcs with respect to the value node. In many cases, however, there is more than one possible node deletion sequence. They all lead to the optimal solution of the problem, but may involve different computational efforts, which is a primary issue when facing real-size models. Finding the optimal deletion sequence is a NP-hard problem. The proposals given in the literature have proven to require complex transformations of the influence diagram. In this paper, we present a genetic algorithm-based approach, which merely has to be added to the influence diagram evaluation algorithm we use, and whose codification is straightforward. The experiments, varying parameters like crossover and mutation operators, population sizes and mutation rates, are analysed statistically, showing favourable results over existing heuristics.     

一种实用的JOB-SHOP生产调度算法

根据生物遗传算法并结合工件的生产工艺知识，提出了一种JOB－SHOP生产调度新算法。该算法采用可编程控制器软件编程的巡回扫描原理，解决了生产调度的仿真问题，所提出的方法为解决生产调度问题提供了新的途径。