随机团队任务分配和定向问题的敏捷相似启发式方法:在无人机中的应用

Javier Panadero, A. Juan, Alfons Freixes, M. Grifoll, C. Serrat, Mohammad Dehghanimohamamdabadi
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引用次数: 0

摘要

无人机的高效协调需要解决具有挑战性的操作问题。其中之一是综合团队任务分配和定向问题(TAOP)。TAOP可以看作是众所周知的团队定向问题(TOP)的延伸。在经典的TOP问题中,一个同质的无人机机队必须选择并访问客户的子集,以最大限度地提高从这些访问中获得的总奖励,同时保证每条航线的最大旅行时间。在TAOP中,必须将许多不同的任务(客户服务)分配给异构无人机机队,同时还必须确定最佳路由计划以覆盖这些服务。由于天气条件等因素可能会影响旅行时间,因此这些因素被建模为随机变量。可靠性问题也被考虑在内,因为随机时间可能会阻止无人机在电池耗尽之前成功完成路线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Agile Simheuristic for the Stochastic Team Task Assignment and Orienteering Problem: Applications to Unmanned Aerial Vehicles
Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.
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