基于智能算法的油田档案管理系统任务分配研究

摘要

In order to solve problems like the low efficiency of operations incurred by the task stacking and frequent overtime in the workflow management system, having adaptive artificial glowworm algorithm and ant colony algorithm combined to form a new intelligent algorithm(AGSO-ACO)was implemented for task alloca-tion of archives management system.Experimental results show that, this AGSO-ACO algorithm can ensure a balance growth of user's total load and bring user's task into correspondence with empirical value as well as make users come to load balancing in a local time period.%为解决工作流管理系统中由任务堆积和超时导致的系统工作效率低的问题,将自适应人工萤火虫算法和蚁群算法结合,形成一种新型智能AGSO-ACO算法,并利用该算法进行油田档案管理系统任务分配.实验结果表明:AGSO-ACO算法可以保证用户总负载均衡增长、用户的任务与经验值基本保持一致、用户在局部时间段内达到负载均衡.