@inproceedings{cb5b483dbb5045cda0a594d92782f661,
title = "Optimization of logistics distribution for gas station convenience stores based on stochastic demand",
abstract = "Taking the logistics distribution optimization of gas station convenience store as the object, this paper studies the mathematical model of vehicle routing problem with time window under the condition of stochastic demands of each customer, and puts forward the genetic algorithm to solve the problem. First, based on the historical data of gas station convenience stores, the demand fluctuation prediction is obtained, and the predicted demand is used for logistics distribution. The demands at each customer are uncertain and follow certain probability distribution, and a chance constrained programming model is established and solved by an improved genetic algorithm. Aiming at the solving process of the algorithm, a crossover operator and a mutation operator adapted to the problem are proposed, which improves the solving speed, solution quality and stability of the algorithm. The feasibility and effectiveness of the model and algorithm are verified by the simulation results.",
keywords = "Gas station convenience store, genetic algorithm, multi-depot, stochastic demand, VRPTW",
author = "Xihui Wang and Renqian Zhang and Wanli Yi",
note = "Publisher Copyright: {\textcopyright} 2025 SPIE.; 2nd International Conference on Optical Communication and Optoelectronic Technology, OCOT 2025 ; Conference date: 18-07-2025 Through 20-07-2025",
year = "2025",
month = nov,
day = "13",
doi = "10.1117/12.3083647",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Klimis Ntalianis",
booktitle = "Second International Conference on Optical Communication and Optoelectronic Technology, OCOT 2025",
address = "美国",
}