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Vehicle Scheduling with Multiple Trips and Time Windows and Long Planning Horizon
Conference proceeding

Vehicle Scheduling with Multiple Trips and Time Windows and Long Planning Horizon

Shudong Liu, Xiaoli Li and Shili Xiang
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.1
01/01/2018

Abstract

Algorithms Automotive parts Genetic algorithms Integer programming Linear programming Mathematical models Mixed integer Production scheduling Rail transportation Scheduling Transportation systems Windows (intervals)
Conference Title: 2018 International Conference on Intelligent Rail Transportation (ICIRT) Conference Start Date: 2018, Dec. 12 Conference End Date: 2018, Dec. 14 Conference Location: Singapore We consider scheduling a vehicle/mobile robot in intelligent material transportation systems with multiple trips, time windows and long planning horizon. We propose a novel approach for the scheduling problem which consists of two parts: a) a framework for splitting the long planning horizon problem into many problems with short planning horizons; b) a fast algorithm for scheduling with short planning horizons based on a flexible and effective two-index mixed integer programming (MIP) model. Numerical results show our algorithm can get optimal solutions in seconds/minutes for the short planning horizon problems for which existing three-index MIP model in literature needs hours or cannot obtain optimal solutions after six hours. For long planning horizon problems, our method is also fast and has good scalability, and can significantly reduce cost compared with the Genetic Algorithm in the literature.

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