Hybrid genetic optimization method of pavement maintenance decision-making for expressway
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摘要: 为了提高高速公路路面养护决策的效率与稳定性, 降低养护成本, 分析了传统数学规划优化方法与遗传算法的适用性, 引入伪并行、最优保存和自适应参数调整策略, 提出了高速公路路面养护决策混合遗传优化方法。仿真结果表明: 混合遗传算法不但收敛速度和搜索能力优于简单的遗传算法, 有效地避免了决策的早熟现象, 而且可以对任意多个高速公路路面养护方案进行养护资金的优化分配, 养护资金总额是没有限制的, 因此, 混合遗传算法很好地解决了高速公路路面养护决策优化问题。Abstract: In order to improve the efficiency and stability of pavement maintenance decision-making for expressway, reduce the cost of pavement maintenance, the applicabilities of traditional mathematics programming method and genetic algorithm were analyzed, pseudo-parallel tactic, optimum preservation tactic and self-adapted parameter adjustment were introduced, and a hybrid genetic optimization method of pavement maintenance decision-making for expressway was put forward.Simulation result shows that the convergence speed and searching ability of the method were better than that of simple genetic algorithm, the premature convergence of pavement maintenance decision-making was overcome, the optimum allocations of maintenance funds were realized aimed at the multi-projects of pavement maintenance, and the investment is infinite, so the method effectively solves the optimization problem of pavement maintenance decision-making for expressway.3 tabs, 11 refs.
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表 1 收敛次数与平均收敛代数
Table 1. Convergence counts and average convergence generations
表 2 在线、离线性能
Table 2. On-line performances and off-line performances
表 3 各方案的投资与效益值
Table 3. Investments and benefits of maintenance schemes
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