Research on Scheduling Optimization of Free-floating Bike Sharing Based on Improved Ant Colony Algorithm

摘要

In order to reduce the transportation cost of enterprises, reduce customer waiting time, aiming at the current problem of resource allocation of shared bicycles, a new mathematical model of ant colony algorithm with soft time window is built, which aims at the lowest transportation cost and the shortest customer waiting time. In this paper, a scheduling strategy based on improved ant colony algorithm is proposed, which improves the search accuracy and global search ability by improving state transition rules, local pheromone and global pheromone update rules. Then an example is given to test the improved ant colony algorithm. The results show that, compared with genetic algorithm and traditional ant colony algorithm, this algorithm greatly reduces the cost of enterprise by 10.1% and 7.7%. Specifically, transportation costs and customer waiting can be reduced. It is conducive to the sustainable development of the industry.