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Online-optimization of multi-elevator transport systems with reoptimization algorithms based on set-partitioning models

机译:基于集划分模型的再优化算法在线优化多电梯运输系统

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摘要

We develop and experimentally compare policies for the control of a system of k elevators with capacity one in a transport environment with l floors, an idealized version of a pallet elevator system in a large distribution center of the Herlitz PBS AG in Falkensee. Each elevator in the idealized system has an individual waiting queue of infinite capacity. On each floor, requests arrive over time in global waiting queues of infinite capacity. The goal is to find a policy that, without any knowledge about future requests, assigns an elevator to each request and a schedule to each elevator so that certain expected cost functions (e.g., the average or the maximal flow times) are minimized. We show that a reoptinnization policy for minimizing average squared waiting times can be implemented to run in real-time (I s) using dynamic column generation. Moreover, in discrete event simulations with Poisson input it outperforms other commonly used policies like multi-server variants of greedy and nearest neighbor. (c) 2006 Elsevier B.V. All rights reserved.
机译:我们开发并实验比较了在l层运输环境中控制容量为k的k个电梯系统的控制策略,该系统是Falkensee的Herlitz PBS AG大型配送中心中的托盘电梯系统的理想版本。理想化系统中的每个电梯都具有无限容量的单独等待队列。在每个楼层,请求会随着时间到达无限容量的全局等待队列中。目标是找到一种策略,该策略无需任何关于未来请求的知识就将电梯分配给每个请求,并将时间表分配给每个电梯,以使某些预期的成本函数(例如,平均或最大流动时间)最小化。我们表明,可以使用动态列生成来实施最小化平均平方等待时间的重新优化策略,以实时运行(I s)。此外,在具有Poisson输入的离散事件模拟中,它的性能优于其他常用策略,例如贪婪和最近邻居的多服务器变体。 (c)2006 Elsevier B.V.保留所有权利。

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