Research on Path Planning Problems Based on Ant Colony Algorithm

With the gradual transfer of China's consumer market from the real economy to the Internet economy, more and more consumers will choose online shopping, the number of express delivery in China has increased more than 10 times within 10 years, and has remained the world's first for many years. In the context of the rapid development of the e-commerce economic industry, China's major logistics industry, although invested a lot of money for continuous renovation and construction, but due to the industry's research is later than the Western developed countries, resulting in the cost of enterprise operation is always high. How to maximize the interests of enterprises is always the most important concern of the logistics industry as a whole. The main content includes: (1) For the vehicle path problem, the model design with minimum cost control, including the addition of time window restrictions and tram delivery restrictions, summarize the mathematical model and explain the model in detail. (2) Explain the operation principle of the ACO algorithm, and simulate the environment in Python platform, including the establishment of coordinate axes, urban path calculation, pheromone creation and updating, as well as the establishment of ACO algorithm model and multiple superposition in order to improve the accuracy of the results. (3) Summarize the experimental data and generalize the data. Synthesize the above models and algorithms to find the optimal distribution path by analyzing the effects of various constraints on the objective function.