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Pseudo-Boolean Optimization in Case of an Unconnected Feasible Set

In: Models and Algorithms for Global Optimization

Author

Listed:
  • Alexander Antamoshkin

    (Siberian State Aerospace University)

  • Igor Masich

    (Siberian State Aerospace University)

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].

Suggested Citation

  • Alexander Antamoshkin & Igor Masich, 2007. "Pseudo-Boolean Optimization in Case of an Unconnected Feasible Set," Springer Optimization and Its Applications, in: Aimo Törn & Julius Žilinskas (ed.), Models and Algorithms for Global Optimization, pages 111-122, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-36721-7_7
    DOI: 10.1007/978-0-387-36721-7_7
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