关键词: 交通运输工程； 多式联运；路径优化；蚁群算法；不确定环境多目标优化；班期

Abstract: Aiming at the multi-modal transport network in uncertain environment, a bi-objective optimization model with minimum total transport cost and duration was constructed by considering the influencing factors such as transshipment cost, duration and transport mode timetable. Monte Carlo (MC) simulation approach was used to deal with the uncertainty of transport network and the multi-objective ant colony algorithm combined with non-dominated sorting was designed to solve the Pareto frontier solution. In order to solve the problem of low solution quality of basic ant colony algorithm caused by slow convergence speed and premature convergence, a direction heuristic factor was added into the state transition strategy, and a “max-min ant system” was introduced in the pheromone update strategy, so as to improve the quality of the solution. Finally, an example was given to verify the optimization efficiency of the improved ant colony algorithm, and five decision paths that fully met their requirements for different goals were provided for the decision-maker.

Key words: traffic and transportation engineering; multi-modal transport; path optimization; ant colony algorithm; multi-objective optimization in uncertain environment; timetable