Open AccessA Hybrid Search Scheduler for Dynamic Auto-driving Team Scheduling with Time Window under Cloud Plan
Author(s) -
Li Ming
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1302/2/022041
Subject(s) - cloud computing , computer science , scheduling (production processes) , ant colony optimization algorithms , distributed computing , plan (archaeology) , architecture , real time computing , artificial intelligence , engineering , operating system , operations management , art , archaeology , visual arts , history
The car cloud plan means that the traveller in the cloud plan does not need to buy an automatic driving vehicle, only need to join the cloud plan, send the travel instruction to the cloud scheduler through the mobile device in hand, and then the cloud scheduler provides the travel service. With the development of actual travel, more and more problems are moving towards the direction of dynamic travel. In this paper, a hybrid solver based on ant colony optimization system search architecture is designed. In the ant colony algorithm, a new algorithm is constructed by combining local search heuristic algorithm with path problem. This paper combines the cloud planning platform with automatic driving vehicle scheduling to quickly collect customer orders and have rapid large-scale processing capabilities, using the order information sent by the traveller to the cloud, through an ant colony searcher to achieve rapid processing of orders.