基于改进蝙蝠算法的柔性流水车间排产优化问题研究
为解决柔性流水车间调度问题(flexible flow shop scheduling problem,FFSP),提出了一种基于精英个体集的自适应蝙蝠算法(self-adaptive elite bat algorithm,SEBA)。针对蝙蝠算法存在求解离散问题具有局限性、易陷入局部极值、优化结果精度低等问题,该算法采用ROV(ranked order value)编码方式,使算法适用于求解离散型的FFSP;提出基于汉明距离的精英个体集,由多个适应度高但相似度低的精英个体轮流引导种群进化,增强种群进化活力,避免寻优过程陷入局部极值;提出自适应位置更新机制,提高算法优化精度。最后采用不同规模...
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Published in | 计算机应用研究 Vol. 34; no. 7; pp. 1935 - 1938 |
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Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
沈阳建筑大学 信息与控制工程学院, 沈阳 110168
2017
中国科学院沈阳自动化研究所 数字工厂研究室, 沈阳 110016 中国科学院网络化控制系统重点实验室, 沈阳 110016 中国科学院网络化控制系统重点实验室, 沈阳 110016%沈阳建筑大学 信息与控制工程学院,沈阳,110168%中国科学院沈阳自动化研究所 数字工厂研究室, 沈阳 110016 |
Subjects | |
Online Access | Get full text |
ISSN | 1001-3695 |
DOI | 10.3969/j.issn.1001-3695.2017.07.003 |
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Abstract | 为解决柔性流水车间调度问题(flexible flow shop scheduling problem,FFSP),提出了一种基于精英个体集的自适应蝙蝠算法(self-adaptive elite bat algorithm,SEBA)。针对蝙蝠算法存在求解离散问题具有局限性、易陷入局部极值、优化结果精度低等问题,该算法采用ROV(ranked order value)编码方式,使算法适用于求解离散型的FFSP;提出基于汉明距离的精英个体集,由多个适应度高但相似度低的精英个体轮流引导种群进化,增强种群进化活力,避免寻优过程陷入局部极值;提出自适应位置更新机制,提高算法优化精度。最后采用不同规模的标准实例对改进算法进行测试,与已有算法进行对比,实验结果验证了改进蝙蝠算法求解FFSP问题的有效性。 |
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AbstractList | 为解决柔性流水车间调度问题(flexible flow shop scheduling problem,FFSP),提出了一种基于精英个体集的自适应蝙蝠算法(self-adaptive elite bat algorithm,SEBA)。针对蝙蝠算法存在求解离散问题具有局限性、易陷入局部极值、优化结果精度低等问题,该算法采用ROV(ranked order value)编码方式,使算法适用于求解离散型的FFSP;提出基于汉明距离的精英个体集,由多个适应度高但相似度低的精英个体轮流引导种群进化,增强种群进化活力,避免寻优过程陷入局部极值;提出自适应位置更新机制,提高算法优化精度。最后采用不同规模的标准实例对改进算法进行测试,与已有算法进行对比,实验结果验证了改进蝙蝠算法求解FFSP问题的有效性。 TP301.6; 为解决柔性流水车间调度问题(flexible flow shop scheduling problem,FFSP),提出了一种基于精英个体集的自适应蝙蝠算法(self-adaptive elite bat algorithm,SEBA).针对蝙蝠算法存在求解离散问题具有局限性、易陷入局部极值、优化结果精度低等问题,该算法采用ROV(ranked order value)编码方式,使算法适用于求解离散型的FFSP;提出基于汉明距离的精英个体集,由多个适应度高但相似度低的精英个体轮流引导种群进化,增强种群进化活力,避免寻优过程陷入局部极值;提出自适应位置更新机制,提高算法优化精度.最后采用不同规模的标准实例对改进算法进行测试,与已有算法进行对比,实验结果验证了改进蝙蝠算法求解FFSP问题的有效性. |
Abstract_FL | In order to solve the flexible flow shop scheduling problem,this paper proposed the SEBA.The existing BA could not solve the discrete problem because it was easily trapped in local extremum and had low accuracy of the optimization results.SEBA adopted the ROV coding method,which made the algorithm suitable for solving discrete FFSP problems.This paper designed the set of the elite individuals based on hamming distance,which had higher fitness and lower similarities.It could also take turns to lead the population evolution,enhance the vitality of population evolution and avoid optimization process trap in local extremum.It designed an adaptive position update method to improve the accuracy of algorithm.Finally,it measured the SEBA by the datas from different scale scheduling benchmark problems with comparison of several algorithms.Simulation results show that SEBA is efficient for solving FFSP. |
Author | 韩忠华 朱伯秋 史海波 林硕 |
AuthorAffiliation | 沈阳建筑大学信息与控制工程学院,沈阳110168 中国科学院沈阳自动化研究所数字工厂研究室,沈阳110016 中国科学院网络化控制系统重点实验室,沈阳110016 |
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Author_FL | Lin Shuo Han Zhonghua Zhu Boqiu Shi Haibo |
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DocumentTitleAlternate | Study for flexible flow shop scheduling problem based on advanced bat algorithm |
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Keywords | bat algorithm elite individual set Hamming distance 蝙蝠算法 精英个体集 汉明距离 柔性流水车间问题 flexible flow shop scheduling problem(FFSP) |
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Notes | 51-1196/TP In order to solve the flexible flow shop scheduling problem, this paper proposed the SEBA. The existing BA could not solve the discrete problem because it was easily trapped in local extremum and had low accuracy of the optimization results. SEBA adopted the ROV coding method, which made the algorithm suitable for solving discrete FFSP problems. This paper designed the set of the elite individuals based on hamming distance, which had higher fitness and lower similarities.It could also take turns to lead the population evolution, enhance the vitality of population evolution and avoid optimization process trap in local extremum. It designed an adaptive position update method to improve the accuracy of algorithm. Finally, it measured the SEBA by the datas from different scale scheduling benchmark problems with comparison of several algorithms. Simulation results show that SEBA is efficient for solving FFSP. Han Zhonghua1,2,3, Zhu Boqiu1, Shi Haibo2,3 , Lin Shuo1 ( 1. Information & Control Engineering Fa |
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SubjectTerms | 柔性流水车间问题 汉明距离 精英个体集 蝙蝠算法 |
Title | 基于改进蝙蝠算法的柔性流水车间排产优化问题研究 |
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