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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Vydáno v:European journal of operational research Ročník 105; číslo 1; s. 224 - 235
Hlavní autoři: Tian, Peng, Ma, Jian, Zhang, Dong-Mo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier 16.02.1998
Elsevier Sequoia S.A
Edice:European Journal of Operational Research
Témata:
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
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Abstract 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.
AbstractList 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.
Author Tian, Peng
Ma, Jian
Zhang, Dong-Mo
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Cites_doi 10.1007/BF01020580
10.1126/science.220.4598.671
10.1109/43.75636
10.1016/0305-0548(86)90048-1
10.1007/BF00339943
10.1007/BF01720032
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Issue 1
Keywords Integer programming
Mixed strategy
Non linear programming
Experimental study
Algorithm
Optimization
Convergence
Polynomial time
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SubjectTerms 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
Title Non-linear integer programming by Darwin and Boltzmann mixed strategy
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