周欣霖　魏奧　王寧寧

摘 要：“共享汽車+軌道交通”可有效改善其他公共交通換乘軌道交通的不足，大大減少私家車數(shù)量，緩解城市道路交通堵塞。本文致力于解決“共享汽車+軌道交通”中用戶可能面臨的在軌道交通站點“無車可用”或“無位可停”的問題，提出自適應(yīng)自主遷移調(diào)度策略，包含共享汽車自主遷移與用戶自主遷移兩種情況，進行用戶預(yù)約時間窗設(shè)計，進一步優(yōu)化共享汽車停放位置。構(gòu)建帶時間窗的“共享汽車+軌道交通”調(diào)度模型，采用遺傳算法提高模型求解效率。通過系統(tǒng)隨機生成的數(shù)據(jù)驗證了模型的有效性和可行性。研究結(jié)果為推進共享汽車與軌道交通換乘接駁的發(fā)展提供理論依據(jù)。

關(guān)鍵詞：“共享汽車+軌道交通” 用戶預(yù)約時間窗 遷移調(diào)度策略 遺傳算法

Proposing and Optimizing the Dispatching Strategy of "Car Sharing + Rail Transit"

Zhou Xinlin，Wei Ao，Wang Ningning

Abstract：“Car sharing + rail transit” can effectively improve the shortcomings of other public transportation transferring to rail transit， greatly reducing the number of private cars， and alleviating urban road traffic congestion. This article is dedicated to solving the problems of “car-free” or “no-stop” in rail transit stations that users may face in “car-sharing + rail transit”， and proposes an adaptive autonomous migration scheduling strategy， including autonomous migration of shared cars and users autonomous migration in both cases， designing the time window for user appointments， and further optimizing the parking location of shared cars. The study constructs a “shared car + rail transit” scheduling model with time windows， and uses genetic algorithms to improve the efficiency of model solving. The data generated randomly by the system verifies the validity and feasibility of the model. The research results provide a theoretical basis for advancing the development of shared cars and rail transit transfers.

Key words：“car sharing + rail transit”， user appointment time window， migration scheduling strategy， genetic algorithm