摘要
为满足电子商务客户多样化和个性化的需求,建立了多车场、多车型的装卸混合车辆调度模型,并使用混合遗传启发式算法求解.首先采用混合编码,使问题变得更简洁;利用个体数量控制选择策略,以保证群体的多样性;引入2-交换变异策略,并结合爬山算法,加强染色体的局部搜索能力.然后,对混合遗传算法求得的精英种群进行禁忌搜索,提高了搜索效率.最后,通过实例计算表明了上述模型和算法的有效性.
In order to satisfy with the individual and various demand of customer under e-commerce, the vehicle scheduling model of picking-delivery for multi-depot and multi-type vehicles is established. Hybrid genetic heuristic algorithm is used to get the optimization solution. Firstly, b^ybrid coding is used to simplify the problem. The individual amount control choice strategy is applied to guard the diversity of group. By introducing 2- exchange mutation operator and combining with hill-climbing algorithm, the partial searching ability of chromosome is increased. Then stock elite derived from the hybrid genetic algorithm is searched with taboo, which improves the searching efficiency of algorithm. Finally, an example shows the effectiveness of the models and methods.
出处
《控制与决策》
EI
CSCD
北大核心
2009年第12期1769-1774,共6页
Control and Decision
基金
国家自然科学基金项目(70801022)
黑龙江省科技攻关项目(GB05D202-3)
关键词
装卸混合的车辆路径问题
多车场
多车型
混合遗传启发式算法
Vehicle routing problem with backhauls
Multi-depot
Multi-type vehicles
Hybrid genetic heuristic algorithm
