A Cooperative Framework for Fireworks Algorithm
نویسندگان
چکیده
منابع مشابه
Fireworks Algorithm for Optimization
Inspired by observing fireworks explosion, a novel swarm intelligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks are also well designed. In order to demonstrate the validation of the FA, a number of experiments ...
متن کاملIntroduction to Fireworks Algorithm
Inspired by fireworks explosion at night, conventional fireworks algorithm (FWA) was developed in 2010. Since then, several improvements and some applications were proposed to improve the efficiency of FWA. In this paper, the conventional fireworks algorithm is first summarized and reviewed and then three improved fireworks algorithms are provided. By changing the ways of calculating numbers an...
متن کاملHybridized Fireworks Algorithm for Global Optimization
In this paper we introduce hybridized fireworks algorithm for global optimization problems. We replaced Gaussian search method from the original fireworks algorithm with the search equation adopted from the firefly algorithm. To test our approach, we implemented six standard bound-constrained benchmarks and performed comparative analysis with the basic fireworks algorithm, as well as with two o...
متن کاملOpposition-Based Adaptive Fireworks Algorithm
A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and ...
متن کاملAdaptive Mutation Dynamic Search Fireworks Algorithm
The Dynamic Search Fireworks Algorithm (dynFWA) is an effective algorithm for solving optimization problems. However, dynFWA easily falls into local optimal solutions prematurely and it also has a slow convergence rate. In order to improve these problems, an adaptive mutation dynamic search fireworks algorithm (AMdynFWA) is introduced in this paper. The proposed algorithm applies the Gaussian m...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Computational Biology and Bioinformatics
سال: 2017
ISSN: 1545-5963
DOI: 10.1109/tcbb.2015.2497227