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Cellular Transport Systems Improved: Achieving Efficient Operations with Answer Set Programming

机译:改进了蜂窝运输系统:通过答案集编程实现高效运营

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Autonomous vehicles for in-plant transportation are widely accepted in the industry nowadays. If applied in order picking, efficiency of their operations is essential for the performance of the overall system. Even though the developed systems are tailored to work in highly volatile environments their procedures are programmed in a comparably old-fashioned and inflexible manner. Answer set programming is experiencing a revival due to advances in the development of solving algorithms and computer hardware. This paper is an invited, extended version of Schieweck et al. (Proceedings of the 9th international joint conference on computational intelligence, 2007, [1]), in which several approaches for the application of answer set programming in order picking systems with autonomous vehicles are discussed. In this paper, the provided information on the approachesis extended, the discussion expanded and the paradigm of reactive answer set programming is additionally taken into account.
机译:如今,用于厂内运输的自动驾驶汽车在业界已被广泛接受。如果用于订单拣选,则其操作效率对于整个系统的性能至关重要。即使已开发的系统是为在高度易变的环境中工作而量身定制的,但其程序却是以相对老式和不灵活的方式进行编程的。由于求解算法和计算机硬件的发展进步,答案集编程正在复兴。本文是Schieweck等人的受邀扩展版本。 (第九届国际计算智能联合会议论文集,2007,[1]),其中讨论了将答案集编程应用到自动驾驶汽车的拣选系统中的几种方法。在本文中,提供了有关方法的信息,扩展了讨论范围,并另外考虑了反应式答案集编程的范式。

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