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FOA: fireworks optimization algorithm

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Abstract

In this paper, a novel meta-heuristic algorithm called Fireworks Optimization Algorithm (FOA) is introduced with few control parameters for discrete and continuous optimization problems. This algorithm is inspired from explosion pyrotechnic devices producing colorful spikes like red, blue and silver. By modelling the explosion behavior of the Fireworks in the sky, the search space can be swept efficiently to find the global optima. To improve the balance between the exploration and exploitation of individuals, three categories are defined to avoid local optimal traps and applied to the search agents. Each category has a different task and predefined updating position rules. A grouping strategy is considered to prevent the algorithm from premature convergence. The performance of FOA is demonstrated over 15 standard benchmarks in the continuous version and 30 images thresholding problems in the discrete version. The obtained results reveal the superiority of the proposed algorithm with fewer input parameters over other state-of-the-art optimization methods in most cases.

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Authors and Affiliations

  1. Electrical Engineering Department, Sirjan University of Technology, Sirjan, Iran

    Ehsan Ehsaeyan

  2. Department of Communication and Electronic Engineering, Shiraz University, Shiraz, Iran

    Alireza Zolghadrasli

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  1. Ehsan Ehsaeyan
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  2. Alireza Zolghadrasli
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Correspondence to Ehsan Ehsaeyan.

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Ehsaeyan, E., Zolghadrasli, A. FOA: fireworks optimization algorithm. Multimed Tools Appl 81, 33151–33170 (2022). https://doi.org/10.1007/s11042-022-13093-7

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