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混合智能算法和双层规划模型在城市交通领域已得到了广泛的应用,且实际效果显著。本文采用基于遗传算法(GA)和模拟退火算法(SA)的GASA混合优化策略求解铁路客票价格问题的双层规划模型,并用一个简单的算例表明:本算法在求解该双层规划方面更好发挥了智能搜索的优势,具有更高的效率和可信度。
Hybrid intelligent algorithm and bilevel programming model have been widely used in the field of urban traffic, and the actual effect is remarkable. In this paper, a two-tier programming model based on Genetic Algorithm (GA) and Simulated Annealing (SA) is proposed to solve the railway ticket price problem using a GASA hybrid optimization strategy. A simple example is given to show that the proposed algorithm is better in solving the bi-level programming problem Take advantage of smart search, with greater efficiency and credibility.