[1]李枝勇,马良,张惠珍.多目标0-1规划问题的蝙蝠算法[J].智能系统学报,2014,9(06):672-676.[doi:10.3969/j.issn.1673-4785.201310038]
 LI Zhiyong,MA Liang,ZHANG Huizhen.Bat algorithm for the multi-objective 0-1 programming problem[J].CAAI Transactions on Intelligent Systems,2014,9(06):672-676.[doi:10.3969/j.issn.1673-4785.201310038]
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多目标0-1规划问题的蝙蝠算法
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年06期
页码:
672-676
栏目:
出版日期:
2014-12-25

文章信息/Info

Title:
Bat algorithm for the multi-objective 0-1 programming problem
作者:
李枝勇 马良 张惠珍
上海理工大学 管理学院, 上海 200093
Author(s):
LI Zhiyong MA Liang ZHANG Huizhen
School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China
关键词:
智能优化组合优化多目标0-1规划问题蝙蝠算法
Keywords:
intelligent optimizationcombinatorial optimizationmulti-objective 0-1 programming problembat algorithm
分类号:
TP301.6;N945
DOI:
10.3969/j.issn.1673-4785.201310038
文献标志码:
A
摘要:
如何获取多目标问题更多的Pareto 最优解具有十分重要的意义。在重新定义蝙蝠位置和速度更新公式的基础上,提出了一种用于求解多目标0-1 规划问题的改进的蝙蝠算法。通过测试函数进行仿真实验,结果表明:与遗传算法、蚁群算法、元胞蚁群算法和粒子群算法相比,所提出的算法能够为多目标0-1 规划问题找到更多的Pareto 解,体现了蝙蝠算法在解决该问题上的有效性和优越性。
Abstract:
Obtaining more Pareto solutions is very important for the multi-objective problem. This paper presented an improved bat algorithm for solving the multi-objective 0-1 programming problem with linear constrains. The proposed algorithm, which is based on redefining the updating formulas of the velocity and position about every bat, is implemented through several tests. The algorithm is compared with a genetic algorithm, an ant colony optimization algorithm, a cellular ant colony algorithm and a particle swarm optimization algorithm. The comparisons showed that the proposed algorithm can get more Pareto solutions and be much more effective to solve such problems.

参考文献/References:

[1] 马良,朱刚,宁爱兵.蚁群优化算法[M]. 北京:科学出版社, 2008: 185-189.
[2] YANG X S. A new metaheuristic bat-inspired algorithm[M]//Nature inspired cooperative strategies for optimization (NICSO 2010). Berlin Heidelberg: Springer, 2010: 65-74.
[3] YANG X S. Bat algorithm for multi-objective optimisation[J]. International Journal of Bio-Inspired Computation, 2011, 3(5): 267-274.
[4] YANG X S, GANDOMI A H. Bat algorithm: a novel approach for global engineering optimization[J]. Engineering Computation, 2012, 29(5): 267-289.
[5] GANDOMI A H, YANG X S, ALAVI A H, et al. Bat algorithm for constrained optimization tasks[J]. Neural Computing and Applications, 2013, 22(6): 1239-1255.
[6] 刘勇,马良,许秋艳.多目标0-1规划问题的元胞蚁群优化算法[J]. 系统工程, 2009, 27(2): 119- 122. LIU Yong, MA Liang, XU Qiuyan. Solving multi-objective 0-1 programming by cellular ant algorithm[J]. Systems Engineering, 2009, 27(2): 119-122.
[7] 韩燕燕,马良,赵小强.多目标0-1规划问题的蜂群算法[J]. 运筹与管理, 2012, 21(2): 23-26. HAN Yanyan, MA Liang, ZHAO Xiaoqiang. Bee colony algorithm for the multi-objective 0-1 programming problem [J]. Operations Research and Management Science, 2012, 21(2): 23-26.
[8] 孙滢,高岳林.一种求解多目标0-1规划问题的自适应粒子群算法[J].计算机应用与软件, 2009, 26(12): 71-73.SUN Ying, GAO Yuelin. An adaptive particle swarm optimization algorithm for solving multi-objective 0-1 programming problem [J]. Computer Application and Software, 2009, 26(12): 71-73.
[9] 杨玲玲,马良,张惠珍.多目标0-1规划的混沌优化算法[J].计算机应用研究, 2012, 29(12): 4486- 4488.YANG Lingling, MA Liang, ZHANG Huizhen. Chaotic optimization algorithm for multi-objective 0-1 programming problem [J]. Application Research of Computers, 2012, 29(12): 4486- 4488.

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备注/Memo

备注/Memo:
收稿日期:2013-9-12;改回日期:。
基金项目:上海市一流学科建设基金资助项目(S1201YLXK);上海高校青年教师培养资助计划资助项目(slg12010);高等学校博士学科点专项科研基金联合资助课题资助项目(20123120120005);上海市教育委员会科研创新基金资助项目(14YZ090);上海市研究生创新基金资助项目(JWCXSL1202);上海理工大学博士科研启动基金资助项目(1D-10-303-002).
作者简介:李枝勇,男,1986年生,硕士研究生,主要研究方向为智能优化、系统工程。发表学术论文9篇;马良,男,1964年生,教授,博士生导师,主要研究方向为智能优化、系统工程。先后承担完成包括国家自然科学基金在内的各类科研项目20多项,发表论文300余篇,出版专著1部,主编教材2部。
通讯作者:李枝勇.Email:lizhiyong.2180869@163.com.
更新日期/Last Update: 2015-06-16