Simultaneous Generalized Hill-Climbing Algorithms for Addressing Sets of Discrete Optimization Problems

This paper introduces simultaneous generalized hill-climbing (SGHC) algorithms as a framework for simultaneously addressing a set of related discrete optimization problems using heuristics. Many well-known heuristics can be embedded within the SGHC algorithm framework, including simulated annealing,...

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Veröffentlicht in:	INFORMS journal on computing Jg. 17; H. 4; S. 438 - 450
Hauptverfasser:	Vaughan, Diane E, Jacobson, Sheldon H, Hall, Shane N, McLay, Laura A
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Linthicum INFORMS 22.09.2005 Institute for Operations Research and the Management Sciences
Schlagworte:	Algorithms Analysis analysis of algorithms Combinatorial probabilities Design optimization Geometric probabilities Heuristic Markov analysis Markov processes Mathematical optimization Methods Probabilities Probability Studies suboptimal algorithms United States
ISSN:	1091-9856, 1526-5528, 1091-9856
Online-Zugang:	Volltext
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