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A particle swarm optimization algorithm for optimal car-call allocation in elevator group control systems

机译:用于电梯群控制系统中最优轿厢分配的粒子群优化算法

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摘要

High-rise buildings require the installation of complex elevator group control systems (EGCSs). In vertical transportation, when a passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group, the EGCS must allocate one of the cars of the group to the hall call. We develop a particle swarm optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm is compared to other soft computing techniques such as genetic algorithm and tabu search approaches that have been proved as efficient algorithms for this problem. The proposed PSO algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better average journey times and computational times compared to genetic and tabu search approaches.
机译:高层建筑需要安装复杂的电梯组控制系统(EGCS)。在垂直运输中,当乘客按下安装在地板上并位于电梯组轿厢附近的层站呼叫按钮进行门厅呼叫时,EGCS必须将组中的其中一辆轿厢分配给门厅呼叫。我们开发了一种粒子群优化(PSO)算法来处理此汽车呼叫分配问题。将PSO算法与其他软计算技术(例如遗传算法和禁忌搜索方法)进行了比较,这些方法已被证明是解决该问题的有效算法。提出的PSO算法在10到24层的高层建筑以及2到6辆汽车的几种轿厢配置中进行了测试。试验结果表明,与遗传搜索和禁忌搜索方法相比,提出的PSO算法具有更好的平均旅行时间和计算时间。

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