Solving the Assignment Problem Using Continuous-Time and Discrete-Time Improved Dual Networks
The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two...
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| Vydáno v: | IEEE transaction on neural networks and learning systems Ročník 23; číslo 5; s. 821 - 827 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York, NY
IEEE
01.05.2012
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2162-237X, 2162-2388, 2162-2388 |
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| Abstract | The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique. |
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| AbstractList | The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique. The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique.The assignment problem is an archetypal combinatorial optimization problem. In this brief, we present a continuous-time version and a discrete-time version of the improved dual neural network (IDNN) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures. Both of them are theoretically guaranteed to be globally convergent to a solution of the assignment problem if only the solution is unique. |
| Author | Xiaolin Hu Jun Wang |
| Author_xml | – sequence: 1 givenname: Xiaolin surname: Hu fullname: Hu, Xiaolin – sequence: 2 givenname: Jun surname: Wang fullname: Wang, Jun |
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| Keywords | Analog circuit Combinatorial problem Analog circuits assignment problem Linear programming Continuous time sorting problem Neural network Combinatorial optimization Quadratic programming Sorting Discrete time Problem solving Mathematical programming |
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| References | ref13 haddad (ref17) 2008 ref14 ref20 li (ref19) 2010; 21 ref22 ref10 hu (ref15) 2009; 39 ref21 liu (ref11) 2009 knuth (ref23) 1973 ref2 ref1 ref16 liu (ref7) 2010; 21 ref18 ref8 kinderlehrer (ref12) 1980 ref4 ref3 ref6 ref5 cichocki (ref9) 1993 |
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| SubjectTerms | Algorithms Analog circuits Applied sciences Artificial intelligence assignment problem Biological neural networks Circuits Combinatorial analysis Computer science; control theory; systems Connectionism. Neural networks Convergence Decision Support Techniques Equations Exact sciences and technology Game Theory Learning Learning systems linear programming Networks Neural networks Neural Networks (Computer) Neurons Optimization Pattern Recognition, Automated - methods quadratic programming sorting problem Trajectory Upper bound |
| Title | Solving the Assignment Problem Using Continuous-Time and Discrete-Time Improved Dual Networks |
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