全局人工鱼群算法求解水果运输调度问题

To Solve Vehicle Routing Problem for Fruits Based on Global Aetificial Fish Swarm Algorithm

分析4种不同的水果运输调度问题(Fruits in Vehicle Routing Problem,FVRP):带硬时间窗的具有需求关联的模型、带容量约束的车辆运输调度问题模型、车辆运输调度问题模型和旅行商问题模型,并构建了相应的数学模型,采用基本人工鱼群算法和全局人工鱼群算法对所建立的4种模型求解,实验证明,全局人工鱼群算法克服了精度低、后期收敛慢、复杂度较高等缺点,能有效地求解此类问题,进一步证明了问题模型的复杂程度影响算法寻优能力,问题模型越复杂,收敛更慢.同时,也体现出当问题模型较复杂时,全局人工鱼群算法的寻优质量和速度优于人工鱼群算法.

Analysed four kinds of FVRP （Fruits in Vehicle Routing Problem）：FVRPHTW （Fruits in Vehicle Routing Problem with Hard Time Windows）, CVRP （Capacitated Vehicle Routing Problem）,VRP （Vehicle Routing Problem） and TSP（Traveling Salesman Problem）, builded the related mathmatical models, adopted BAFSA （basic artificial fish swarm algorithm） and GAFSA （global artificial fish swarm algorithm） to solve these models, the results showed that GAFSA could overcome these shortcomings, such as low precision, slow rate of convergeneeat later period and high complexity, etc. Moreover, the algorithm was flexible to solve the kinds of problems. It could make further efforts to proved that the complexity of model could affect the ability of searching the optimum solution, the more complex of the model, the slower convergence. Moreover, when problem model was more complex, the optimization quality and speed of GAFSA was better than BAFSA.