免疫遗传算法在柔性Job-shop调度问题中的应用

Immune genetic algorithm applied to flexible job shop scheduling

借鉴生物免疫机理提出了一种求解柔性Job shop车间调度问题的免疫遗传算法.仿真结果表明,该算法有效地避免了传统遗传算法中因选择压力过大造成早熟现象的发生,显著地提高了遗传算法(GA)对全局最优解的搜索能力和收敛速度,这将使遗传算法在众多实际的优化问题上具有更广泛的应用前景.

A kind of immune genetic algorithm is introduced to dispose flexible Job-shop scheduling problem. The simulations show that the algorithm can effectively avoid the premature convergence problem caused by the high selective pressure. Moreover, it improves the ability of searching an optimum solution and increases the convergency speed. The algorithm should have extensive application prospect in many practical optimization problems.