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本文分析了编组站到发线占用特性,在前人对于到发线运用建模的基础上,建立更适合于编组站到发线的运用模型。由于到发线的安排属于NPC问题,本文综合遗传算法与模拟退火算法的优点对该模型进行求解,采用混合算法——模拟退火遗传算法(SAGA),来提高运行效率和解的质量,并在目标函数上以及在约束条件上提出新的理论,引入惩罚因子以加快算法模型的收敛。文中阐述了该算法的具体实现过程,并通过模拟仿真对算法进行了验证,结果表明该模型算法是可靠和有效的。
This paper analyzes the occupancy characteristics of marshalling station to the departure line. Based on the predecessors’ modeling of departure lane, this paper establishes a more suitable model for marshalling station to departure lane. Because the hairline arrangement is an issue of NPC, this paper sums up the advantages of Genetic Algorithm and Simulated Annealing Algorithm to solve this model. The hybrid algorithm - Simulated Annealing Genetic Algorithm (SAGA) is used to improve the efficiency of operation and the quality of solution. Put forward a new theory on the function and constraints, and introduce the penalty factor to speed up the convergence of the algorithm model. The paper describes the concrete realization process of the algorithm and verifies the algorithm through simulation. The results show that the algorithm is reliable and effective.