Solving inequality constrained combinatorial optimization problems by the hopfield neural networks

The Hopfield neural networks are extended to handle inequality constraints where linear combinations of variables are lower- or upper-bounded. Then by eigenvalue analysis, the effects of the inequality constraints are analyzed and the following results are obtained: (a) if a combinatorial solution o...

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Veröffentlicht in:	Neural networks 1992, Vol.5 (4), p.663-670
Hauptverfasser:	Abe, Shigeo, Kawakami, Junzo, Hirasawa, Kotaroo
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Combinatorial optimization Electric, optical and optoelectronic circuits Electronics Energy function Equality constraints Exact sciences and technology Hopfield model Inequality constraints Knapsack problem Neural networks Weight
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