首页> 外文会议>Evolutionary Multi-Criterion Optimization; Lecture Notes in Computer Science; 4403 >Designing Traffic-Sensitive Controllers for Multi-Car Elevators Through Evolutionary Multi-objective Optimization
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Designing Traffic-Sensitive Controllers for Multi-Car Elevators Through Evolutionary Multi-objective Optimization

机译:通过进化多目标优化设计多轿厢电梯的交通敏感控制器

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Multi-Car Elevator (MCE) that has several elevator cars in a single shaft attracts attention for improvement of transportation in high-rise buildings. However, because of lack of experience of such novel systems, design of controller for MCE is very difficult engineering problem. One of the promising approaches is application of evolutionary optimization to from-scratch optimization of the controller through discrete event simulation of the MCE system. In the present paper, the authors propose application of evolutionary multi-objective optimization to design of traffic-sensitive MCE controller. The controller for MCE is optimized for different traffic conditions in multi-objective way. By combining the multi-objective optimization with the exemplar-based policy (EBP) representation that has adequate flexibility and generalization ability as a controller, we can successfully design a controller that performs well both in the different traffic conditions and works adequately by generalization in the conditions not used in the optimization process.
机译:在单个竖井中具有多个电梯轿厢的多轿厢电梯(MCE)引起了人们对改善高层建筑交通的关注。然而,由于缺乏这种新颖系统的经验,用于MCE的控制器的设计是非常困难的工程问题。一种有前途的方法是通过MCE系统的离散事件仿真将进化优化应用于控制器的从零开始优化。在本文中,作者提出了进化多目标优化在交通敏感型MCE控制器设计中的应用。 MCE的控制器以多目标方式针对不同的交通状况进行了优化。通过将多目标优化与具有足够灵活性和泛化能力的基于样例的策略(EBP)表示相结合,作为控制器,我们可以成功设计出一种控制器,该控制器在不同的交通状况下均能很好地工作,并且通过泛化来充分发挥作用优化过程中未使用的条件。

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