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A fuzzy programming method for optimization of autonomous logistics objects

机译:一种用于优化自主物流对象的模糊规划方法

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Recently several studies have explored the realization of autonomous control in production and logistic operations. In doing so, it has been tried to transmit the merit of decision-making from central controllers with offline decisions to decentralized controllers with local and real-time decision makings. However, this mission has still some drawbacks in practice. Lack of global optimization is one of them, i.e., the lost chain between the autonomous decentralized decisions at operational level and the centralized mathematical optimization with offline manner at tactical and strategic levels. This distinction can be reasonably solved by considering fuzzy parameters in mathematical programming to meet the required tolerances for autonomous objects at operational level. This claim is recommended and partially experimented in this paper. An assembly scenario is modeled by a discrete-event simulation, in which autonomous pallets carry products throughout the system. This scenario is optimized with regard to its objectives in a simulation, while fuzzy parameters in optimization programming can consider autonomous decisions done at operational level.
机译:最近几项研究探讨了在生产和物流运营中实现了自主控制。在这样做时,已经尝试从中央控制器传递决策的优点,其中与具有本地和实时决策的分散控制器的离线决策。然而,这种任务在实践中仍然存在一些缺点。缺乏全球优化是其中之一,即运营层面自主分散决策与在战术和战略层面的离线方式的集中数学优化之间的丢失链。通过考虑数学规划的模糊参数,可以合理地解决了这种区别,以满足运行级别的自主对象所需的公差。本文建议并部分尝试此索赔。组装方案是由离散事件仿真建模的,其中自主托盘在整个系统中携带产品。这种情况在模拟中的目标方面进行了优化,而优化编程中的模糊参数可以考虑在运营级别完成的自主决策。

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