中文摘要：

在管理实践中广泛存在的分组优化问题大多是强NP—Hard问题，求解难度较大．针对制造企业供应物流决策中合并运输的分组优化问题，设计了基于整数编码的组群遗传算法．在简单直观的整数编码方式下，提出了两点组群杂交以及基于适应值的组群启发式变异等遗传算子，实现了面向组群的进化过程，为求解复杂的多约束、非线性的分组优化问题提供了新的方法．该算法应用于物流决策实践，与基于BSD的启发式算法相比较，检验了算法的性能和参数设置．

英文摘要：

Grouping proble Hard. This paper propose optimization problem with were designed to realize th ing mutation. It was appli the performance of the alg m exists widely in management, it is hard to solve because of its strong NP Hard This paper proposed number-coded grouping genetic algorithm, a new solution to supply logistics constraints and nonlinear objective function. Several grouping-based operators e grouping evolution, such as two-point grouping crossover and heuristic grouped to a real-world numerical case in transportation consolidation, which shows orithm.