摘要
在研究不确定生产调度问题的基础上,针对具有模糊加工时间和模糊交货期的调度问题给出了作业车间模糊调度模型,用三角模糊数表示模糊加工时间,梯形模糊数表示模糊交货期,以交货期平均满意度最大作为调度目标。针对模糊调度问题对基本蚁群算法作了改进,并给出了新的状态转移规则,同时采用自适应信息素更新策略使算法能快速跳出局部收敛,进行仿真结果验证了自适应蚁群算法求解作业车间模糊调度的有效性。
On the basis of studying uncertainties in the production scheduling problem, we present the Job shop fuzzy scheduling model for the scheduling problem with fuzzy processing time and fuzzy due date. In the present model, fuzzy processing time and fuzzy due date are denoted by triangular fuzzy numbers and Trapezoid fuzzy numbers respectively, and the scheduling goal is the greatest satisfaction of average delivery. To address the fuzzy scheduling problem, we have improved the basic ant colony algorithm and present a new state transition rules, at the same time use adaptive pheromone updating strategy that can quickly get out of part convergence. The simulation results show that adaptive ant colony algorithm is effective to solve Job Shop fuzzy scheduling problem.
出处
《计算机仿真》
CSCD
北大核心
2009年第4期244-248,共5页
Computer Simulation
关键词
作业车间调度
不确定性
模糊调度问题
自适应蚁群算法
Job shop scheduling
uncertainty
Fuzzy scheduling problem
Adaptive ant colony algorithm
