带时间窗和同时送取货的车辆路径问题模型及算法

Research on vehicle routing problem model and algorithm with time window and simultaneous delivery

研究了带时间窗和同时送取货的车辆路径问题,建立相应的数学模型,并在量子进化算法的基础上,提出一种新的改进量子算法.为了得到高质量的初始解,通过定义满载率和向心角,设计了带有回场权重的初始解生成方案.同时,通过定义量子元胞体、互换量子α位与β位等方法,尝试解决量子进化算法中有效信息丢失严重的问题,为解决量子域、二进制域及问题域之间的映射问题提供一种思路.最后,选取Wang和Chen测试数据集,对算法性能进行有效性测试.

The paper studies the vehicle routing problem with time window and simultaneous delivery,establishes the corresponding mathematical model,and proposes a new improved quantum algorithm based on quantum evolutionary algorithm.In order to obtain a high-quality initial solution,the author designed an initial solution generation scheme with return-to-center weights by defining the full load rate and the centripetal angle.At the same time,the author attempts to solve the problem of serious information loss in quantum evolutionary algorithms by defining quantum cell bodies,exchanging quantumα-bits andβ-bits,and provides a solution to the problem of mapping between quantum domains,binary domains and problem domains.Finally,the Wang and Chen test data sets are selected to test the effectiveness of the algorithm.