Branch Strategy and Deletion Strategy Matching on Interval Global Optimization Algorithm

Nowadays, the computing capability is increasing steadily. It has gradually become possible to solve the global optimization problem of complex function. For the global optimization solution, the requirements of correctness and completeness have become more sophisticated. This paper presents a deter...

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Hauptverfasser: Xuening Fan, Yongmei Lei, Ronggang Jia
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Nowadays, the computing capability is increasing steadily. It has gradually become possible to solve the global optimization problem of complex function. For the global optimization solution, the requirements of correctness and completeness have become more sophisticated. This paper presents a deterministic algorithm - branch strategy and deletion strategy matching on interval global optimization algorithm (BMD).This algorithm aims at a kind of function who has first-order continuous function in its search domain. This method execute deterministic search in the search range, and can get the calculation results of the deterministic algorithm. Its computational amount is less than the current deterministic algorithm and random algorithms. It can reduce the computational amount and speed up the convergence under the premise of finding the exact global optimal solution without increasing memory consumption.
DOI:10.1109/CIT.2012.212