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An improved cuckoo search algorithm for multi-objective optimization. (English) Zbl 1399.90302

Summary: The recently proposed cuckoo search algorithm is an evolutionary algorithm based on probability. It surpasses other algorithms in solving the multi-modal discontinuous and nonlinear problems. Searches made by it are very efficient because it adopts Lévy flight to carry out random walks. This paper proposes an improved version of cuckoo search for multi-objective problems (IMOCS). Combined with nondominated sorting, crowding distance and Lévy flights, elitism strategy is applied to improve the algorithm. Then numerical studies are conducted to compare the algorithm with DEMO and NSGA-II against some benchmark test functions. Result shows that our improved cuckoo search algorithm convergences rapidly and performs efficiently.

MSC:

90C59 Approximation methods and heuristics in mathematical programming
90C29 Multi-objective and goal programming

Software:

SPEA2; MOPSO
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Full Text: DOI

References:

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