用鱼群算法求解多级递阶物流中转运输系统优化问题

建立了解决多级递阶物流中转运输系统优化问题的大规模非线性最优规划模型。在优化模型中，在兼顾变量约束条件的空间限制和求解精度的情况下将求解空间离散化，方法是将变量空间划分成一定大小的网格，各级中转站的最优位置将在限定区域内的一些已知点上选取。该问题维数太高，采用改进的鱼群算法对该问题进行了求解。在算法中建立了各级中转站与网格点关系矩阵和相邻两级中转站间的关系矩阵来消除约束条件和压缩变量数；使用了基于相似性的演化算法来融合全局搜索和局部搜索；使用了自适应delta变异算子、双算术交叉算子、峰跳操作算子等多种算子改进人工鱼的各种行为。应用结果表明，该算法计算速度、可靠性和稳定性大幅度提高。

Optimization of multilevel hierarchical transshipment system in logistics transportation based on fish-swarm algorithm

A large-scale nonlinear optimum programming model to solve the optimization problem of multilevel hierarchical transshipment system in logistical transportation was established.In the optimization model,the solving space was discretized based on actual consideration of space constraints of variables and precision of solutions;the policy of discretization was to create grids with certain size within space of variables,and the optimal locations for all transfer stations at each level of a multilevel hierarchical transshipment system were selected from all known coordinate points.Because the dimension of the model was enormous,an improved fish-swarm algorithm was used to solve the problem.In the improved algorithm,two matrices describing the relation between transfer stations of all levels with angular points of grids and the relation between two adjacent levels' transfer stations were established to delete constraints and compress greatly variables of the model;an evolutionary algorithm based on evolutionary similarity was applied to mix the basic properties of global and local search;the self-adaptive delta variation operator,dual arithmetic crossover operator,peak-jump operator were used to improve the behaviors of artificial fish-swarm algorithm.An application result shows that the speed and reliability of the optimization algorithm is improved greatly.