Hybrid Flower Pollination Algorithm For Solving Global Optimization Problems

doi:10.3969/j.issn.1006-2475.2019.10.010

Abstract

Abstract: Metaheuristic algorithms can be used as an effective tool for finding near-optimal solutions. Therefore, it is necessary to improve metaheuristic algorithms and enhance the algorithm’s performance. This paper introduces an enhanced variant of Flower Pollination Algorithm (FPA)，which combines FPA with Extremal Optimization(EO) to form the FPA-EO. The FPA-EO algorithm makes use of the global search capability of FPA and the local search capability of EO, and applies it to 11 benchmark functions to test the new algorithm. At the same time, the algorithm is compared with other four famous optimization algorithms: standard flower pollination algorithm (FPA), bat algorithm (BAT), firefly algorithm (FA), and simulated annealing algorithm(SA). The comprehensive results show that the algorithm can find a more accurate solution than the other four algorithms.

Key words: metaheuristic algorithms, extremal optimization algorithm, enhanced variant, hybrid algorithm

CLC Number:

TP301

ZHU Yang-yang. Hybrid Flower Pollination Algorithm For Solving Global Optimization Problems[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.10.010.

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