Intermodal Path Optimization Based on Mixed Algorithm
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摘要: 为了求解联合运输网络的最优运输方式组合问题,采用遗传算法并使用整数编码方式对城市节点进行编码,摒弃了传统的二进制编码方式,有效地缩减了编码长度并简化了编解码工作;城市节点链的运输方式组合与节点间运输方式转换使用动态规划方法来确定;至于联合运输网络数据,在建立多重图数据结构基础上,采用结构体数组与链式存储结构相结合的方式来存储。通过仿真实验表明,该方法可行,能够在较短的时间和可预期的迭代次数内找到最优解。Abstract: In order to find the best combination of transport modes in an intermodal network ,a genetic algorithm is presented and the key connection joints in a city are coded into integer numbers instead of the traditional binary digits . This can reduce the length of the code and simplify the coding work .The collocation of transport modes at the connection joints and the transfer of transport modes can be studied by dynamic programming .The intermodal network data are stored by array of structure and linked storage structure based on the multi-graph structure .This method is found to be feasible in simulation ,capable of finding the optimum solutions in a very short time and with a small number of iterations .
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Key words:
- multi-graph /
- path optimization /
- data structure /
- genetic algorithm /
- dynamic programming /
- intermodal transport
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