Abstract: Heterogeneous open vehicle routing problem is logistics optimization indispensable part. According to the standard genetic algorithm shortcomings of slowly convergent speed, weakly partial searching ability and easily premature, hybrid heuristic algorithm is used to optimize the solution. The paper uses sequence of real numbers coding so as to simplify the problem, constructs the targeted initial solution to improve the feasibility, adopts a choice based on sort of a combination with the best retention strategies to ensure the diversity of population, and uses some arithmetic crossover operator to enhance whole search ability of the chromosome. Using Boltzmann simulated annealing mechanism for controlling genetic algorithm crossover and mutation operations, it improves the convergence speed and search efficiency. Finally, the good performance can be proved by experiment calculation and concrete examples.

Key words: heterogeneous open vehicle routing problem, sequence of real numbers coding, some arithmetic crossover operator, Boltzmann simulated annealing mechanism, hybrid heuristic algorithm

摘要： 多车型开放式车辆路线问题，是物流配送优化中不可缺少的环节。针对标准遗传算法存在收敛速度慢，局部搜索能力差，易早熟的缺点，采用混合启发式算法进行优化求解。采用实数序列编码，使问题变得更简洁；有针对性地构建初始解，提高了解的可行性；用基于排序的选择与最佳保留相结合策略，保证群体的多样性；引入部分算术交叉算子，加强染色体的全局搜索能力；利用模拟退火算法的Boltzmann机制，控制遗传算法的交叉、变异操作，提高了算法的收敛速度和搜索效率。仿真结果表明混合启发式算法在求解质量和计算效率上好于标准遗传算法。

关键词: 多车型开放式车辆路线问题, 实数序列编码, 部分算术交叉算子, Boltzmann机制, 混合启发式算法