Non-linear integer programming by Darwin and Boltzmann mixed strategy

Non-linear integer programming is an NP-complete problem with extensive theoretical and practical backgrounds. Based on the proposed Darwin and Boltzmann mixed strategy, a general stochastic iterative algorithm for the NIP problems is presented. The algorithm synthesizes the advantages of the Darwin...

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Veröffentlicht in:European journal of operational research Jg. 105; H. 1; S. 224 - 235
Hauptverfasser: Tian, Peng, Ma, Jian, Zhang, Dong-Mo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier 16.02.1998
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
Algorithms
Applied sciences
Exact sciences and technology
Integer programming
Mathematical programming
Nonlinear programming
Operational research and scientific management
Operational research. Management science
Operations research
Studies
Integer programming
Mixed strategy
Non linear programming
Experimental study
Algorithm
Optimization
Convergence
Polynomial time
ISSN:0377-2217, 1872-6860
Online-Zugang:Volltext
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Zusammenfassung:Non-linear integer programming is an NP-complete problem with extensive theoretical and practical backgrounds. Based on the proposed Darwin and Boltzmann mixed strategy, a general stochastic iterative algorithm for the NIP problems is presented. The algorithm synthesizes the advantages of the Darwin strategy and the Boltzmann annealing strategy. It converges asymptotically to the global optimums and has shown to be polynomial in complexity. The experimental evaluations also show that the proposed algorithm is more efficient than the simulated annealing algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(97)00024-6