Ant Colony Algorithm Improvement of AGV Path Based on Soft Time Window for Waste Tobacco Recovery

摘要

According to the site layout of cigarette industry and the requirement of AGV soft time window for waste tobacco recycling, the change of demand for waste tobacco recycling based on soft time window ant colony algorithm is proposed. The method is based on the waste smoke recovery centered on the unit station, Considering the influence of the actual production rhythm of complex Workshop on the recovery demand time, the membership function of the time when AGV arrives at the waste smoke recovery station is used to characterize the satisfaction of the unit station to the timeliness of the waste smoke recovery business. Therefore, with the average satisfaction of AGV arrival time as the constraint condition and the minimum cost of recycling time as the objective, an optimization model of smoke recycling path with fuzzy soft time window is established, and the model is solved by ant colony algorithm. The validity and robustness of the path optimization model are verified by an example.