公开(公告)号：US11875271B2

公开(公告)日：2024-01-16

申请号：US17024917

申请日：2020-09-18

Applicant: XIANGTAN UNIVERSITY

Inventor： Juan Zou ,  Qite Yang ,  Tingrui Pei ,  Jinhua Zheng ,  Haibo Li ,  Shengqi Chen ,  Xiao Yang ,  Shengxiang Yang

IPC: G06N3/08 ,  G06N3/126 ,  G06N3/086 ,  G06F111/06

CPC classification number: G06N3/126 ,  G06N3/086 ,  G06F2111/06

Abstract: The present invention provides a method and a system for train periodic message scheduling based on a multi-objective evolutionary algorithm, relating to the field of information and communications technology, mainly including: acquiring an MVB periodic message table; binary encoding the MVB periodic message table and initializing it randomly, to generate an iterative population; performing crossover and mutation operations on the individuals of the iterative population using a genetic algorithm, to update the iterative population; constructing an MVB periodic scheduling table that meets scheduling needs and minimizes the macro cycle according to a multi-objective algorithm and the updated iterative population; scheduling train periodic messages according to the MVB periodic scheduling table, thereby meeting the real-time requirement of periodic data transmission in actual scheduling scenarios.

公开(公告)号：US20210089929A1

公开(公告)日：2021-03-25

申请号：US17024917

申请日：2020-09-18

Applicant: XIANGTAN UNIVERSITY

Inventor： Juan Zou ,  Qite Yang ,  Tingrui Pei ,  Jinhua Zheng ,  Haibo Li ,  Shengqi Chen ,  Xiao Yang ,  Shengxiang Yang

IPC: G06N3/12 ,  G06Q10/04 ,  G06N3/08 ,  G06Q10/06 ,  G06F111/06

Abstract: The present invention provides a method and a system for train periodic message scheduling based on a multi-objective evolutionary algorithm, relating to the field of information and communications technology, mainly including: acquiring an MVB periodic message table; binary encoding the MVB periodic message table and initializing it randomly, to generate an iterative population; performing crossover and mutation operations on the individuals of the iterative population using a genetic algorithm, to update the iterative population; constructing an MVB periodic scheduling table that meets scheduling needs and minimizes the macro cycle according to a multi-objective algorithm and the updated iterative population; scheduling train periodic messages according to the MVB periodic scheduling table, thereby meeting the real-time requirement of periodic data transmission in actual scheduling scenarios.