摘要
对基于蚁群算法的车间作业调度问题求解进行了研究,在分析了传统蚁群算法求解车间作业调度问题容易出现早熟、收敛于局部最优解以及搜索速度慢的缺陷,提出了一种改进的混合蚁群算法。该方法在信息素更新规则上利用信息素局部更新策略和全局更新策略来进行信息素的更新,并将领域搜索与蚁群算法相结合,从而求得问题的可行解。最后,基于benchmarks问题进行了实验仿真,实验结果证明该改进混合算法的有效性及可行性。
First,the thesis researches the solving of the Job Shop Scheduling Problem（JSSP） based on the Ant Colony Algorithm（ACA）,and analyses the faults of the solving of the JSSP based on the traditional ACA,such as easy earliness,converging local optimal solution and search speed solw,the thesis puts an improved hybrid Ant Colony Algorithm.This algorithm carries out the update by using the pheromone update rule on the local pheromone update strategy and the global pheromone update strategy,and combines the field of search and ACA,and then obtains a feasible solution of the problem.Finally,the thesis gives the experimental simulation based on the Benchmark problems,the experimental results demonstrate the validity and feasibility of the improved hybrid ant colony algorithm.
出处
《计算机与数字工程》
2011年第1期4-6,52,共4页
Computer & Digital Engineering
基金
河南省教育厅基础研究项目(编号:2003520261)资助
关键词
车间作业调度问题
蚁群算法
局部更新
全局更新
job shop scheduling problem
ant colony algorithm
local update
global update
