摘要
考虑到粒子群算法的高搜索效率和模拟退火算法的局部搜索能力,提出了采用粒子群和模拟退火的混合算法求解机加工工艺线平衡问题的方法。针对机加工过程实际约束条件的特点,提出了一种改进的编码和解码方式,使得离散的编码序列与连续的微粒位置及速度迭代进化对应起来,并给出粒子约束修正的方法,使得粒子更新后总能满足约束条件,加快了算法的收敛速度。最后以某柴油发动机缸体机缸体加工生产线为例,验证了该方法的有效性。
Considering high efficient searching ability of PSO and local searching capability of SA, a hybrid PSO algorithm for solving the problem of machining processes balancing was proposed. Aiming at the characteristics of operations order and clamping constraints, an improved way of encoding and decoding was presented, which makes the coding sequence of discrete matches with the iterative evolution of continuous particle position and speed, at the same time, a method of dealing with such operational constraints was also stated, which makes the updated particles always satisfy the constraints, the convergence rate of the algorithm was improved greatly. Finally, a case of diesel engine cylinder block machining production line was illustrated to prove the validity of the proposed method.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2014年第2期16-21,共6页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家工信部科技重大专项资助项目(2011ZX0415-022)
关键词
发动机缸体
生产线平衡
节拍
模拟退火算法
混合粒子群算法
Engine cylinder block Production line balancing Cycle time Simulated annealingalgorithm Hybrid particle swarm algorithm