【作者】 常俊林； 梁君燕； 魏巍；

【Author】 CHANG Junlin,LIANG Junyan,WEI Wei School of Information and Electrical Engineering,China University of mining and technology,Xuzhou 221008,P.R.China

【机构】 中国矿业大学信息与电气工程学院；

【摘要】 将人工免疫系统融入到粒子群算法中,针对以平均流经时间和最大完工时间为目标的置换流水线调度问题提出了一种双目标免疫粒子群算法(BIPSO)。该算法在粒子群算法的基础上采用动态适应度函数来评价粒子,改进了算法的惯性因子,并利用免疫算法能较好保持种群多样性等优势来弥补粒子群易于陷入局部最优的缺点。仿真实验表明该算法有效地加快了收敛速度,提高了解的质量。更多还原

【Abstract】 An Immune-PSO(BIPSO) algorithm introducing the artificial immune system is proposed for the permutation flow shop scheduling problem with average through time and makespan criterions.In the basis of PSO algorithm,the new algorithm uses dynamic fitness to evaluates particles,improves the inertial factor and compensates the shortcoming of easily falling into the local optimum of the PSO with the advantage of maintaining the diversity of the population of immune algorithm.The simulation results shows that the new method has better performances in the convergence rate and solution quality.更多还原