Solving the Multiobjective Multiple Traveling Salesmen Problem Using Membrane Algorithm

被引:0
作者
He, Juanjuan [1 ]
机构
[1] Wuhan Univ Sci & Technol, Sch Comp Sci, Wuhan 420081, Peoples R China
来源
BIO-INSPIRED COMPUTING - THEORIES AND APPLICATIONS, BIC-TA 2014 | 2014年 / 472卷
关键词
Evolutionary multiobjective optimization; Membrane algorithm; Multiple traveling salesmen problem; NEURAL P SYSTEMS; INSPIRED ALGORITHM; OPTIMIZATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The multiple traveling salesmen problem (mTSP) is a generalization of the classical traveling salesman problem (TSP). The mTSP is more appropriate for real-life applications than the TSP, however, the mTSP has not received the same amount of attention. Due to the high complexity of the mTSP, a more efficient algorithm proposed for mTSP must be based on a global search procedure. Membrane algorithms are a class of hybrid intelligence algorithms, which has been introduced recently as a global optimization technique. In this work, a new membrane algorithm for solving mTSP with different numbers of salesmen and problem sizes is described. The experiment results are compared with several multiobjective evolutionary strategies.
引用
收藏
页码:171 / 175
页数:5
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