配装-运输集成决策模型及其遗传算法

为了充分利用运输工具的装载力和优化运输路径,在充分考虑货物重量、体积及车辆装载力等约束条件下,建立配装 运输集成决策模型并用基于自然数编码的遗传算法对其求解.通过对高复杂度条件下的“遗传特性”分析,算法采用最大保留交叉及自适应交叉变异,最大限度地保留了父代的优良特性,改善基本遗传的“早熟”特性、增强算法的寻优能力并提高了解的精准度.编制了运行平稳的计算机程序,实例计算表明：配装-运输集成决策模型及算法可行有效,不仅使配送总行程节约了26.6%,而且使车辆载重量和体积平均利用率分别达到88%和86%.

Integrated decision model for goods loading-transportation and its genetic algorithm

To make full uses of transportation means' loading-capacity and optimize the transportation path, with full consideration of the restraints of cargo weight and volume as well as loading-capacity, an integrated loading-transportation model was established, and to solve it, the genetic algorithm based on decimal coding was adopted. Through analysis to hereditary property under high complexity condition and adopting both maximum preserved crossover operator and adaptive crossover mutation, the algorithm not only furthest retains the parents' excellent properties and improves the basic genetic algorithm's premature properties, but also builds up the simple genetic algorithm's optimization capabilities and enhances the solution's accuracy. Program for the model was programmed and run smoothly. The example analysis and calculation result show that the integrated loading-transportation model and its solution algorithm are feasible and effective: it not only saves 26.6% of total path, but also makes the average utilization of loading-capacity and volume reach 88% and 86% respectively．