Due to this fact, it may be found that the likelihood of the first automobile in the first line being chosen at this time is 86.6%, while the likelihood of the first automotive within the second line being chosen is just 13.4%. From such analysis, it can be concluded that the usage probability of the second line at a certain second is far smaller than the utilization likelihood of the primary line. And the influence of vacation interval might be inferred by a perform , which relies on time as effectively. On this algorithm, the precedence of every course of will depend on the service time and the time waiting for service. As a way to further optimize the trip rationality of your complete parallel line, this paper optimizes the complete scheduling algorithm primarily based on the original HRRN scheduling idea and turns it into a probability-primarily based dynamic priority scheduling algorithm. Aiming at the issue of optimizing the allocation of taxi resource, this paper relies on the price-profit analysis methodology to determine the factors that affect the taxi driver’s resolution-making.

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