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摘要: 针对流水车间作业调度问题, 提出了一种基于``alldifferent''约束的混合进化算法(Hybrid particle and genetic algorithm, HPGA), 将粒子群算法、遗传操作及模拟退火策略有效地结合在一起. 为了提高算法的求解质量, 引入了一种随机邻域搜索策略. 最后将此算法在不同规模的实例上进行了测试, 并与其他几种最近提出的具有代表性的算法进行了比较. 结果表明, 无论是在求解质量还是收敛速度方面都优于其他几种算法.Abstract: A hybrid particle and genetic algorithm (HPGA) based on the ``alldifferent'' constraint is proposed to solve the flowshop scheduling problem, which combines the particle swarm optimization algorithm, genetic operators, and annealing strategy together. To improve the algorithm's performance further, a neighborhood based local search strategy is proposed and introduced into HPGA. Finally, the HPGA is tested on different scale benchmarks and compared with the recently proposed efficient algorithms. The result shows that both the solution quality and the stability of the HPGA precede the other two algorithms.
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Key words:
- Flowshop scheduling /
- partical swarm optimization (PSO) /
- mutation
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