Human-machine Collaborative Decision-making for Transportation Scheduling Optimization
The paper proposes a human-machine collaborative decision-making methodology based on the deficit function model to solve transportation scheduling problems with flexible constraints.The methodology mainly consists of two stages.In the first stage,by making use of mathematical programming models and the powerful computing capacity of computers,a feasible solution is quickly obtained.In the second stage,with the help of the deficit function model,human beings'own knowledge and experience are employed to further optimize the feasible solution obtained in the first stage,while taking into account flexible constraints.The two stages interact in real time through a graphical user interface composed of deficit function figures,thereby realizing human-machine collaborative decision-making.The effectiveness of the proposed human-machine collaborative decision-making methodology based on the deficit function model is demonstrated through two case studies,i.e.,app-based customized bus scheduling problem and civil aviation aircraft scheduling problem.Computation results show that the proposed methodology can realize the automatic construction of vehicle/flight chains and the automatic insertion of deadheading trips.It is useful for solving complex transportation scheduling problems with flexible constraints.
system engineeringhuman-machine collaborative decision-makingdeficit functiontransportation schedulinginteractive optimization
NETL
NSTL
万方数据
维普
