A Survey on Recurrent Neural Network based model for solving the Assignment Problem

被引:0
作者
Valeri, Kangabam [1 ]
Singh, L. Surajlannar [1 ]
Tongbram, Simon [2 ]
Adhikari, Shuma [2 ]
机构
[1] NIT Manipur, Dept ECE, Imphal 795004, Manipur, India
[2] NIT Manipur, Dept EE, Imphal 795004, Manipur, India
来源
2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT) | 2019年
关键词
Assignment problem; Recurrent Neural Network; Types of RNN; PAN; DAN; IDNN;
D O I
10.1109/i2ct45611.2019.9033671
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Assignment problem refers is the way of calculating a problem by assigning certain quantity of work to equal quantity of work handles inorder to obtain utmost optimized results. It occurs when one manages to solve a large problem to obtain optimized results and in the meantime fulfilling all the related constraints. Numerous ways on how assignment problem is solved has already been found but with the use of Recurrent Neural Network is a complete game changer. Although assignment problem is a method for optimizing a problem, incorporating Recurrent Neural Network leads to a more reliable, efficient and faster way of finding the most optimized result of the problem. This review is based on how assignment problem is solved effectively by using Recurrent Neural Network and discusses the various types of Recurrent Neural Network used in depth.
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页数:4
相关论文
共 25 条
[1]  
Basirzadeh H., 2012, Applied Mathematical Sciences, V6, P2345
[2]  
Bazaraa M.S., 1990, LINEAR PROGRAMMING N, DOI DOI 10.1002/0471787779
[3]   LEARNING LONG-TERM DEPENDENCIES WITH GRADIENT DESCENT IS DIFFICULT [J].
BENGIO, Y ;
SIMARD, P ;
FRASCONI, P .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1994, 5 (02) :157-166
[4]  
Dempe S., 2002, FDN BILEVEL PROGRAMM
[5]   A Recurrent Neural Network for Solving Bilevel Linear Programming Problem [J].
He, Xing ;
Li, Chuandong ;
Huang, Tingwen ;
Li, Chaojie ;
Huang, Junjian .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (04) :824-830
[6]   COMPUTING WITH NEURAL CIRCUITS - A MODEL [J].
HOPFIELD, JJ ;
TANK, DW .
SCIENCE, 1986, 233 (4764) :625-633
[7]   An Improved Dual Neural Network for Solving a Class of Quadratic Programming Problems and Its k-Winners-Take-All Application [J].
Hu, Xiaolin ;
Wang, Jun .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2008, 19 (12) :2022-2031
[8]  
Hu Xiaolin, 2012, IEEE T NEURAL NETWOR, V23
[9]   An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem [J].
Jin, HD ;
Leung, KS ;
Wong, ML ;
Xu, ZB .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2003, 33 (06) :877-888
[10]  
Karush W., 1939, THESIS