用于模具编程的病毒进化遗传算法  

Virus Evolution Genetic Algorithm for Mould Programming

作　　者：原思聪[1] 邹存范[1] 严卫东[1] 江祥奎[2] 

机构地区：[1]西安建筑科技大学机电工程学院,西安710055 [2]西安邮电学院自动化学院,西安710121

出　　处：《计算机工程》2012年第8期252-255,259,共5页Computer Engineering

基　　金：国家"十二五"科技支撑计划基金资助重点项目(2011BAJ02B02-02);陕西省自然科学基金资助项目(2007E218);陕西省科技攻关计划基金资助项目(2011K10-18);陕西省教育厅自然科学专项基金资助项目(09JK559)

摘　　要：针对模具编程的任务规划问题,提出一种编程任务规划算法。以工期、质量和编程人员负载均衡等为目标,建立多目标优化模型,结合病毒进化遗传算法的横向搜索能力和非支配排序遗传算法Ⅱ(NSGA-Ⅱ)的精英保留策略,求取多样性解,引入多种群思想解决多目标问题。仿真结果表明,该算法求得的近似解分布均匀且多样性较好,与NSGA-Ⅱ相比,其解的分布离最优解的前端更加接近。In the paper, a programming task planning for the problem of mould programming task planning is presented, a multi-objective optimization model for duration, quality and programmer load balancing is built. Horizontal search ability of virus evolution genetic algorithm and elite reservation strategy of Non-dominated Sorting Genetic Algorithm- 11 （NSGA- lI ） are adopted for better solutions with diversity. Multi-group strategy is introduced for solving multi-objective problem. Simulation result shows that approximate solution of the algorithm has good distribution and diversity is better, and compared with the NSGA- H, the solution distribution for the algorithm is more close to the front of the optimal solution.

关 键 词：编程任务规划 多目标优化 病毒进化遗传算法 负载均衡 暴露程度 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]