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技术站广义动态配流问题是在综合考虑优先排空和优先发送较近编组去向车流的编组要求、欠轴列车停运要求,以及到发列车在时间和车流接续关系的基础上,将静态配流和列车解编方案调整进行协同优化。分别以阶段内出发列车数最多、出发车辆数最多、车辆在站平均中转时间最短为目标,考虑解体、编组调机能力限制,到发列车车流接续,列车编组计划和列车运行图的影响约束,建立该问题的优化模型。针对问题机理,设计求解这一问题的遗传算法:运用启发式规则生成初始群体;运用倒数算子计算适应度函数,对各目标进行无量纲化和同向化处理;采用轮赌盘选择算子、基于顺序的杂交算子、逆转变异算子和精英保护策略。通过对算例的实验分析,表明该算法的实用性和计算的高效性。
Technical station generalized dynamic distribution problem is to take into account the prioritized emptying and priority to send closer to the formation of the traffic grouping requirements, the requirements of undercarriage outage, as well as train to train in the time and traffic continue to follow the relationship between the static distribution and Coordination and optimization of train readjustment plan. Considering that the number of departure train, the number of departure vehicles and the shortest average transit time of vehicles in the station are the targets respectively, the influences of disintegration, limitation of marshalling capacity, succession of train arrival to train departure, train marshalling plan and train operation map are separately considered. Establish an optimization model of the problem. Aiming at the problem mechanism, a genetic algorithm to solve this problem is designed. Heuristic rules are used to generate the initial population. The reciprocal operator is used to calculate the fitness function, and the objects are dimensionless and co-oriented. , Order-based crossover operator, inverse mutation operator and elite protection strategy. The experimental analysis of the example shows that the algorithm is practical and computationally efficient.