[1]谷文祥,李向涛,朱 磊,等.求解流水线调度问题的万有引力搜索算法[J].智能系统学报,2010,5(5):411-418.[doi:10.3969/j.issn.1673-4785.2010.05.006]
GU Wen-xiang,LI Xiang-tao,ZHU Lei,et al.A gravitational search algorithm for flow shop scheduling[J].CAAI Transactions on Intelligent Systems,2010,5(5):411-418.[doi:10.3969/j.issn.1673-4785.2010.05.006]
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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第5期
页码:
411-418
栏目:
学术论文—智能系统
出版日期:
2010-10-25
- Title:
-
A gravitational search algorithm for flow shop scheduling
- 文章编号:
-
1673-4785(2010)05-0411-08
- 作者:
-
谷文祥,李向涛,朱 磊,周俊萍,胡艳梅
-
东北师范大学 计算机学院,吉林 长春 130117
- Author(s):
-
GU Wen-xiang, LI Xiang-tao, ZHU Lei, ZHOU Jun-ping, HU Yan-mei
-
Department of Computer Science, Northeast Normal University, Changchun 130117, China
-
- 关键词:
-
万有引力搜索算法; 流水线调度; 局部搜索算法; 边界变异; 最大排序规则; 最大完工时间
- Keywords:
-
gravitational search algorithm; flow shop scheduling; local search; boundary mutation; largest rank rule; production time minimizing
- 分类号:
-
TP301.6
- DOI:
-
10.3969/j.issn.1673-4785.2010.05.006
- 文献标志码:
-
A
- 摘要:
-
研究了以最大完工时间为目标的流水线调度问题,使用万有引力算法求解调度问题,提出了一种最大排序规则,利用物体间各个位置分量值存在的大小次序关系,并结合随机键编码的方法产生,将物体的连续位置转变成了一个可行的调度方案;提出了一种边界变异的策略使得越界的物体不再聚集在边界上,而是分布在边界附近的可行空间内,从而增加种群的多样性;结合交换算子和插入算子提出了一种新的局部搜索算法,有效地避免了算法陷入局部最优值,进一步提高了解的质量.最后证明了算法的收敛性,并且计算了算法的时间复杂度和空间复杂度,仿真实验说明了所得算法的有效性.
- Abstract:
-
An improved gravitational search algorithm (IGSA) was proposed to solve the flow shop scheduling problem with the objective of minimizing production time. First, to make a GSA suitable for permutation of the flow shop scheduling problem (PFSSP), a new largest-rank-rule based on a random key was introduced to convert the continuous position of the GSA into the discrete job permutation so that the GSA could be used for solving PFSSP. Second, a new boundary mutation was proposed. This operation stopped the agents which have mutations as a result of using the above method from gathering at the border. They were distributed at a feasible distance from the boundary. This improvement also improved the population diversity. Third, by combining the communicating operator and inserting operator, the new local search was designed to help the algorithm escape from the local minimum. Finally, the convergence of the iterative algorithm and its complexities in time and space were proven. Additionally, simulations and comparisons based on PFSSP benchmarks were carried out, which show that the proposed algorithm is both effective and efficient.
备注/Memo
收稿日期:2010-03-29.
基金项目:国家自然科学基金资助项目(60473042, 60573067, 60803102).
通信作者:李向涛. E-mail: lixt314@nenu.edu.cn.
作者简介:
谷文祥,男,1947年生,教授、博士生导师,主要研究方向为智能规划与规划识别、形式语言与自动机、模糊数学及其应用.参加或承担国家自然科学基金、教育部重点项目、省科委项目多项,发表学术论文100余篇.
李向涛,男,1987年生,硕士研究生,主要研究方向为智能规划、智能信息处理.
朱 磊,男,1987年生,硕士研究生,主要研究方向为智能规划、智能信息处理.
更新日期/Last Update:
2010-11-26