采矿工业两级供应链中的协调生产计划建模

对由一个矿山和一个选矿厂构成的采矿工业两级供应链中的协调生产计划问题进行了研究,建立了相应的线性规划模型·模型的特点是:①集成采选两个环节的生产计划;②将运输问题集成到生产计划中·模型的目标追求供应链总成本最小·模型适用于由一个矿山和一个选厂所组成的两级供应链或者采选联合企业,且能够较容易地扩展到多个矿山和多个选厂的供应链结构·给出了算例以说明模型的应用·结果表明:能够为矿山和选矿厂的协调生产提供决策支持,能够节省总的生产和运输成本,有潜在的应用价值·     

Parallel Frequent Pattern Discovery： Challenges and Methodology

Parallel frequent pattern discovery algorithms exploit parallel and distributed computing resources to relieve the sequential bottlenecks of current frequent pattern mining （FPM） algorithms. Thus, parallel FPM algorithms achieve better scalability and performance, so they are attracting much attention in the data mining research community. This paper presents a comprehensive survey of the state-of-the-art parallel and distributed frequent pattern mining algorithms with more emphasis on pattern discovery from complex data （e.g., sequences and graphs） on various platforms. A review of typical parallel FPM algorithms uncovers the major challenges, methodologies, and research problems in the field of parallel frequent pattern discovery, such as work-load balancing, finding good data layouts, and data decomposition. This survey also indicates a dramatic shift of the research interest in the field from the simple parallel frequent itemset mining on traditional parallel and distributed platforms to parallel pattern mining of more complex data on emerging architectures, such as multi-core systems and the increasingly mature grid infrastructure.