基于协同遗传算法的车间调度问题研究  

Improved Coordinating Genetic Algorithm for Job-Shop Scheduling Problem

作　　者：谌湘倩[1] 戴冬[1] 

机构地区：[1]河南机电高等专科学校计算机科学与技术系,河南新乡453000

出　　处：《河南机电高等专科学校学报》2013年第5期20-23,共4页Journal of Henan Mechanical and Electrical Engineering College

基　　金：河南省教育厅科学技术研究重点项目(12A520017)

摘　　要：遗传规划在实际问题中的应用是一个新的发展方向。文章根据车间调度问题的特点,对遗传规划算法进行了改进,借鉴了一种新编码策略将变长编码变成定长,减少了算法复杂度,提高了运算效率;同时设计了一种新的标记交叉算子,这种交叉算法可以有效地避免产生非法解。由于遗传规划问题的收敛性不高,文中将遗传规划和遗传算法有效地结合起来,提出一种协同遗传规划算法,实验表明,改进后的算法比传统算法能更有效地解决车间调度问题。Application of genetic programming in practical problems is a new development direction . In this paper ,according to the characteristics of job shop scheduling problems ,genetic programming al-gorithm is improved ,using a new coded strategy will be variable length code into a fixed length ,reduce the complexity of the algorithm ,improve the computational efficiency ;at the same time ,design a new marker of crossover operator ,the crossover algorithm can effectively avoid illegal solutions .The conver-gence of genetic programming is not high ,the genetic programming and genetic algorithm are combined effectively ,this paper proposes a cooperative genetic programming algorithm ,experiments show that , the improved algorithm is more effective than the traditional algorithm to solve the job shop scheduling problem .

关 键 词：遗传规划 遗传算法 车间作业调度 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]