Job Shop调度问题的遗传退火算法

针对作业车间(JobShop)调度问题,提出了一个遗传退火算法。该算法构造了基于工作的遗传算子,因而保证了遗传进程中生成个体的可行性,有效地解决了工件机器顺序的约束限制。通过对最佳个体进行模拟退火,把模拟退火机制引入到遗传进化过程中,将模拟退火和遗传算法两者的优点有机地结合起来,从而进一步提高了算法的全局寻优能力。仿真计算表明了该算法的良好收敛性和有效性。

Genetic annealing algorithm for job shop scheduling

A genetic annealing algorithm is proposed for job shop scheduling problem. By constructing job-based genetic operators, this algorithm ensures that each chromosome is feasible in the genetic process, and treats the machine sequence constraint effectively. By simulated annealing of the best chromosome, simulated annealing mechanism is introduced into genetic evolution process, the advantages of both simulated annealing and genetic algorithms are combined effectively, thus improving the global searching ability of the algorithm. Simulation experiment shows the good convergence and effectiveness of this algorithm.