Abstract :
The problem of vehicle routing optimization is researched, to improve the efficiency of vehicle scheduling. With the increasing complexity of the traffic network, the vehicle will face the interference of accident and congestion, this situation is random and cannot be predicted. The traditional vehicle routing planning model lack of analysis of the interference risk, accurate model cannot be established, the vehicle scheduling operating efficiency is bad. In order to avoid these defects, the vehicle routing optimization method is proposed based on hybrid algorithm. According to the theory of traffic information feedback method, the feedback model of road information is established. It provides basis for vehicle routing optimization. The ant colony algorithm and extreme optimization algorithm are combined, the hybrid algorithm is obtained. According to the theory of hybrid algorithm, the vehicle routing optimization model is constructed, and related vehicle data is input in the model. The vehicle routing optimization processing is realized. The experiment results show that this algorithm can improve the scheduling efficiency, so as to meet the actual demand of traffic management.
Keywords :
ant colony optimisation; road accidents; road safety; road traffic control; scheduling; vehicle routing; ant colony algorithm; extreme optimization algorithm; hybrid algorithm; road information feedback model; traffic accident interference risk; traffic congestion interference risk; traffic information feedback method theory; traffic management; traffic network complexity; vehicle routing optimization problem; vehicle routing planning model; vehicle scheduling operating efficiency improvement; Algorithm design and analysis; Job shop scheduling; Optimization; Roads; Vehicle routing; Vehicles; hybrid algorithm; path optimization; vehicle scheduling;
