MARKOVIAN NEURAL NETWORKS

被引：12

作者：

KOVACIC, M

机构：

[1] Faculty of Electrical and Computer Engineering, Ljubljana, YU-61000

来源：

BIOLOGICAL CYBERNETICS | 1991年 / 64卷 / 04期

关键词：

D O I：

10.1007/BF00199598

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The neural network that efficiently and nearly optimally solves difficult optimization problems is defined. The convergence proof for the Markovian neural network that asynchronously updates its neurons' states is also presented. The comparison of the performance of the Markovian neural network with various combinatorial optimization methods in two domains is described. The Markovian neural network is shown to be an efficient tool for solving optimization problems.

引用

收藏

页码：337 / 342

页数：6

相关论文

共 13 条

[1] SELF-ORGANIZING FEATURE MAPS AND THE TRAVELING SALESMAN PROBLEM [J].

ANGENIOL, B ;

VAUBOIS, GD ;

LETEXIER, JY .

NEURAL NETWORKS, 1988, 1 (04) :289-293

[2] THE N-CITY TRAVELING SALESMAN PROBLEM - STATISTICAL-MECHANICS AND THE METROPOLIS ALGORITHM [J].

BONOMI, E ;

LUTTON, JL .

SIAM REVIEW, 1984, 26 (04) :551-568

[3]

Coffman Jr E. G., 1973, OPERATING SYSTEMS TH

[4] AN EVOLUTIONARY APPROACH TO THE TRAVELING SALESMAN PROBLEM [J].

FOGEL, DB .

BIOLOGICAL CYBERNETICS, 1988, 60 (02) :139-144

[5] SOLVING A COMBINATORIAL PROBLEM VIA SELF-ORGANIZING PROCESS - AN APPLICATION OF THE KOHONEN ALGORITHM TO THE TRAVELING SALESMAN PROBLEM [J].

FORT, JC .

BIOLOGICAL CYBERNETICS, 1988, 59 (01) :33-40

[6]

Garey M. R., 1979, COMPUTERS INTRACTABI

[7]

HOPFIELD JJ, 1985, BIOL CYBERN, V52, P141

[8] OPTIMIZATION BY SIMULATED ANNEALING [J].

KIRKPATRICK, S ;

GELATT, CD ;

VECCHI, MP .

SCIENCE, 1983, 220 (4598) :671-680

[9] COMPUTER SOLUTIONS OF TRAVELING SALESMAN PROBLEM [J].

LIN, S .

BELL SYSTEM TECHNICAL JOURNAL, 1965, 44 (10) :2245-+

[10] EFFECTIVE HEURISTIC ALGORITHM FOR TRAVELING-SALESMAN PROBLEM [J].

LIN, S ;

KERNIGHAN, BW .

OPERATIONS RESEARCH, 1973, 21 (02) :498-516