关键词: 城市交通, 行车计划, 自适应大邻域搜索算法, 电动公交, 分时电价, 多车型

Abstract: This paper proposes an optimization model for electric bus scheduling and charging scheduling with the consideration of time-of-use electricity pricing policy and multiple vehicle types, aiming to minimize the total operation cost of electric bus system. The practical operational constraints of bus schedule chain formulation, charging time window, and limited number of chargers are considered in the model. An adaptive large neighborhood search (ALNS) algorithm is proposed to solve the bus schedule optimization problem. This algorithm incorporates diverse destruction and repair operators tailored to the characteristics of the problem, such as the trip-to-vehicle allocation and the feasibility of the bus schedule chain under multiple vehicle types. For the feasible bus schedule chain combinations generated by ALNS, the charging schedule optimization subproblem under time-of-use electricity price is constructed and mapped into a dedicated network. An algorithm based on the minimum-cost-flow is designed to solve for the charging duration, which leads to an optimal decision on charging start time. The model and algorithm are validated using three bus routes in Beijing. The results show that compared with the current situation, the fleet size is reduced from 30 to 24 vehicles, resulting in a decrease in electricity cost and total operation cost by 25.84% and 20.63%, respectively. Comparative experiments are conducted to explore the impact of different weights of repair indicators and combinations of vehicle types on the optimization results.

Key words: urban traffic, bus scheduling, adaptive large neighborhood search, battery electric bus, time-of-use electricity price, multiple vehicle types