Optimization under uncertainty is a challenging topic of practical importance in the Process Systems Engineering.Since the solution of an optimization problem generally exhibits high sensitivity to the parameter varia...Optimization under uncertainty is a challenging topic of practical importance in the Process Systems Engineering.Since the solution of an optimization problem generally exhibits high sensitivity to the parameter variations, the deterministic model which neglects the parametric uncertainties is not suitable for practical applications. This paper provides an overview of the key contributions and recent advances in the field of process optimization under uncertainty over the past ten years and discusses their advantages and limitations thoroughly. The discussion is focused on three specific research areas, namely robust optimization, stochastic programming and chance constrained programming, based on which a systematic analysis of their applications, developments and future directions are presented. It shows that the more recent trend has been to integrate different optimization methods to leverage their respective superiority and compensate for their drawbacks. Moreover, data-driven optimization, which combines mathematical programming methods and machine learning algorithms, has become an emerging and competitive tool to handle optimization problems in the presence of uncertainty based on massive historical data.展开更多
This paper introduces a solution to the secure requirement for digital rights management （DRM） by the way of geospacial access control named geospacial access control （GeoAC） in geospacial field. The issues of aut...This paper introduces a solution to the secure requirement for digital rights management （DRM） by the way of geospacial access control named geospacial access control （GeoAC） in geospacial field. The issues of authorization for geospacial DRM are concentrated on. To geospacial DRM, one aspect is the declaration and enforcement of access rights, based on geographic aspects. To the approbation of digital geographic content, it is important to adopt online access to geodata through a special data infrastructure （SDI）. This results in the interoperability requirements on three different levels： data model level, service level and access control level. The interaction between the data model and service level can be obtained by criterions of the open geospacial consortium （OGC）, and the interaction of the access control level may be reached by declaring and enforcing access restrictions in GeoAC. Then an archetype enforcement based on GeoAC is elucidated. As one aspect of performing usage rights, the execution of access restrictions as an extension to a regular SDI is illuminated.展开更多
This paper presnts a team-oriented programming method specially designed for multiple mobile robots. The team, which is a typical constitution structure in multi-robot system, forms after the user selects suitable rob...This paper presnts a team-oriented programming method specially designed for multiple mobile robots. The team, which is a typical constitution structure in multi-robot system, forms after the user selects suitable robots, assigns their roles and sets related parameters. Team behavior module are introduced for the team-level behavior description and the temporal chain of these modules, realized by finite state automata, partitions the team tasks into discrete operating states and triggers. A graphical programming tool is designed for the team task description with visual diagrams. The real robots experiment of adaptive formation shows the system＇s usability and effectivity.展开更多
文摘Optimization under uncertainty is a challenging topic of practical importance in the Process Systems Engineering.Since the solution of an optimization problem generally exhibits high sensitivity to the parameter variations, the deterministic model which neglects the parametric uncertainties is not suitable for practical applications. This paper provides an overview of the key contributions and recent advances in the field of process optimization under uncertainty over the past ten years and discusses their advantages and limitations thoroughly. The discussion is focused on three specific research areas, namely robust optimization, stochastic programming and chance constrained programming, based on which a systematic analysis of their applications, developments and future directions are presented. It shows that the more recent trend has been to integrate different optimization methods to leverage their respective superiority and compensate for their drawbacks. Moreover, data-driven optimization, which combines mathematical programming methods and machine learning algorithms, has become an emerging and competitive tool to handle optimization problems in the presence of uncertainty based on massive historical data.
基金Funded by the Large-Scale Security SoC Project of Wuhan Science and Technology Bureau of China (No. 20061005119).
文摘This paper introduces a solution to the secure requirement for digital rights management （DRM） by the way of geospacial access control named geospacial access control （GeoAC） in geospacial field. The issues of authorization for geospacial DRM are concentrated on. To geospacial DRM, one aspect is the declaration and enforcement of access rights, based on geographic aspects. To the approbation of digital geographic content, it is important to adopt online access to geodata through a special data infrastructure （SDI）. This results in the interoperability requirements on three different levels： data model level, service level and access control level. The interaction between the data model and service level can be obtained by criterions of the open geospacial consortium （OGC）, and the interaction of the access control level may be reached by declaring and enforcing access restrictions in GeoAC. Then an archetype enforcement based on GeoAC is elucidated. As one aspect of performing usage rights, the execution of access restrictions as an extension to a regular SDI is illuminated.
基金国家高技术研究发展计划(863计划)，the National Natural Science Foundation of China
文摘This paper presnts a team-oriented programming method specially designed for multiple mobile robots. The team, which is a typical constitution structure in multi-robot system, forms after the user selects suitable robots, assigns their roles and sets related parameters. Team behavior module are introduced for the team-level behavior description and the temporal chain of these modules, realized by finite state automata, partitions the team tasks into discrete operating states and triggers. A graphical programming tool is designed for the team task description with visual diagrams. The real robots experiment of adaptive formation shows the system＇s usability and effectivity.
