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Pseudo-Boolean Optimization in Case of an Unconnected Feasible Set

  • Alexander Antamoshkin
  • Igor Masich
Part of the Optimization and Its Applications book series (SOIA, volume 4)

Abstract

Unconstrained pseudo-Boolean optimization is an issue that studied enough now. Algorithms that have been designed and investigated in the area of unconstrained pseudo-Boolean optimization are applied successfully for solving various problems. Particularly, these are local optimization methods [AL97, AM04a, PS82] and stochastic and regular algorithms based on local search for special function classes [ASSSO, BSV02, WW02]. Moreover, there is a number of algorithms for optimization of functions given in explicit form: Hammer’s basic algorithm that, was introduced in [HR68] and simplified in [BHO2]; algorithms for optimization of quadratic functions [AFLS0l, FH00, HS89], etc. Universal optimization methods are also used successfully: genetic algorithms, simulated annealing, tabu search [Gol89, Sch95].

Keywords

Local Search Greedy Algorithm Constraint Function Accessible Region Unimodal Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Alexander Antamoshkin
    • 1
  • Igor Masich
    • 1
  1. 1.Siberian State Aerospace UniversityKrasnoyarskRussia

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