Research on Bus Scheduling Optimization Considering Exhaust Emission Based on Genetic Algorithm: Taking a Route in Nanjing City as an Example

Abstract

In order to enhance passenger willingness to choose buses for commuting and to reduce the operating costs and tailpipe emissions of bus companies, a bus scheduling model is established. The model aims to minimize the sum of the operating costs of the bus company, the costs associated with the loss of passengers’ interest, and the cost of tailpipe emissions. It considers constraints such as maintaining an average load factor of the buses above 60%, ensuring a departure interval of greater than 5 min during non-peak hours and less than 30 min during peak hours, and limiting the maximum number of buses allocated to a route. The passenger flow is divided into peak hours and nonpeak hours according to the survey of passenger flow during each period of a bus operation on a route in Nanjing City, China. A genetic algorithm is employed to solve the proposed bus scheduling model and determine the total costs during peak and non-peak hours. After designing the parameters of the genetic algorithm, optimal departure intervals and bus numbers for a day’s operation cycle on a given route are calculated using a weighting method.