Analyzing the performance of simultaneous generalized hill climbing algorithms

Simultaneous generalized hill climbing (SGHC) algorithms provide a framework for using heuristics to simultaneously address sets of intractable discrete optimization problems where information is shared between the problems during the algorithm execution. Many well-known heuristics can be embedded w...

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Veröffentlicht in:	Computational optimization and applications 2007-05, Vol.37 (1), p.103-119
Hauptverfasser:	Vaughan, Diane E, Jacobson, Sheldon H, Kaul, Hemanshu
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Climbing Heuristic Laboratories Markov analysis Mathematical models Methods Neighborhoods Optimization Optimization algorithms Probability Random variables Studies
Online-Zugang:	Volltext
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