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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

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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.
Research on Scheduling Optimization Model of Intelligent RGV Based on Simulated Annealing Algorithm
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 tar-get requirements under the expected working conditions.

process systemsimulated annealing algorithmscheduling optimizationsimulation

叶飞、李棚

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六安职业技术学院 信息与电子工程学院,安徽 六安 237005

工序系统 模拟退火算法 调度优化 仿真

2024

洛阳师范学院学报
洛阳师范学院

洛阳师范学院学报

CHSSCD
影响因子:0.219
ISSN:1009-4970
年,卷(期):2024.43(8)