基于模拟退火算法的智能有轨制导车辆的调度优化模型研究  

Research on Scheduling Optimization Model of Intelligent RGV Based on Simulated Annealing Algorithm

作　　者：叶飞[1] 李棚[1] Ye Fei;Li Peng(School of Information and Electronic Engineering,Lu’an Vocational and Technical College,Lu’an 237005,China)

机构地区：[1]六安职业技术学院信息与电子工程学院,安徽六安237005

出　　处：《洛阳师范学院学报》2024年第8期27-30,共4页Journal of Luoyang Normal University

基　　金：安徽省教育厅研究项目(gxgnfx2021195);安徽省高等学校科学研究项目(2022AH052496)。

摘　　要：为了解决单、双工序系统作业问题,基于启发式算法中的模拟退火算法来求解RGV(有轨制导车辆)的最优路径.通过模拟真实的系统作业场景,增强了RGV调度策略的稳定性,并构建了带有故障处理机制的RGV调度优化模型.研究结果表明,基于模拟退火算法的智能RGV调度优化模型能够有效满足预期工况下的目标需求.This research aims to solving the optimal path of RGV(rail-guided vehicle)based on the simulated annealing algorithm in the heuristic algorithm to solve the problem of single and double process system operation By simulating the real system operation scenario,the researchers strengthened the stability of RGV scheduling strategy and constructed the RGV scheduling optimization model with fault handling mechanism.The result shows that the intelligent RGV scheduling optimization model based on simulated annealing algorithm can effectively meet the target requirements under the expected working conditions.

关 键 词：工序系统 模拟退火算法 调度优化 仿真 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]