摘要
港口散货物流中,在考虑铲车能力约束条件下合理的铲车调度将提高整体的运作效率,并增强顾客满意度。通过分析货位上待服务的货车与有能力约束的铲车之间的关系,提出了利用主—从级遗传算法解决该类有能力约束的铲车调度问题。首先,建立了以缩短顾客停留时间为目标的数学模型。其次,设计了主、从递阶型式的两级遗传算法。算法中,主级求解铲车到货位的分配问题,从级求解主级所分配铲车能力约束下的货车服务次序及服务时间。另外,为避免非可行解产生,在主从级遗传算法的解码中均设计了启发式规则和惩罚函数。最后,通过一个应用实例的对比实验分析验证了此算法的有效性,并将最优解通过甘特图的形式展现出来。
In port bulk cargo logistics,reasonable forklift truck operation considering forklift truck capacity constraints will improve the whole operational efficiency and increase customers＇ satisfaction.A Genetic Algorithm（GA） with master-slave structure was proposed to solve the forklift truck with capacity constraints dispatching in port bulk cargo logistics.First,a mathematical model was built for the goal to shorten trucks＇ time from arriving to leaving the yard on the basis that a forklift truck with capacity constraints will serve a truck and a truck must be served by one forklift.Then,a real coded GA with master-slave structure and its decoding method were proposed after the analysis of forklifts with capacity constraints and trucks.In addition,when coded in slave structure,heuristic rules and penalty function were designed in order to avoid infeasible solutions.Finally,an application example was used to demonstrate the effectiveness of the proposed algorithm.And the Gantt chart was used to show the optimal strategy when dispatching trucks with capacity constraints.
出处
《计算机应用》
CSCD
北大核心
2012年第6期1741-1744,1748,共5页
journal of Computer Applications
基金
河北省科技支持计划重点项目(092156030)
河北省自然科学基金资助项目(G2010000165)
河北省高等学校自然科学青年基金资助项目(2011125)
关键词
铲车调度
遗传算法
能力约束
优化
forklift truck dispatching
Genetic Algorithm（GA）
capacity constraint
optimization
