A new biologically inspired global optimization algorithm based on firebug reproductive swarming behaviour
| Autor: | Venkataraman Muthiah-Nakarajan, Advait Sanjay Trivedi, Mathew Mithra Noel, Geraldine Bessie Amali |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
biology Basis (linear algebra) business.industry Computer science Heuristic (computer science) General Engineering Swarm behaviour 02 engineering and technology Firebug biology.organism_classification Evolutionary computation Computer Science Applications 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Artificial intelligence Bollinger Bands business Global optimization |
| Zdroj: | Expert Systems with Applications. 183:115408 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2021.115408 |
| Popis: | A new biologically inspired derivative-free global optimization algorithm called Firebug Swarm Optimization (FSO) inspired by reproductive swarming behaviour of Firebugs (Pyrrhocoris apterus) is proposed. The search for fit reproductive partners by individual bugs in a swarm of Firebugs can be viewed naturally as a search for optimal solutions in a search space. This work proposes a mathematical model for five different Firebug behaviours most relevant to optimization and uses these behaviours as the basis of a new global optimization algorithm. Performance of the FSO algorithm is compared with 17 popular heuristic algorithms on the Congress of Evolutionary Computation 2013 (CEC 2013) benchmark suite that contains high dimensional multimodal as well as shifted and rotated functions. Statistical analysis based on Wilcoxon Rank-Sum Test indicates that the proposed FSO algorithm outperforms 17 popular state-of-the-art heuristic global optimization algorithms like Guided Sparks Fireworks Algorithm (GFWA), Dynamic Learning PSO (DNLPSO), and Artificial Bee Colony Bollinger Bands (ABCBB) on the CEC 2013 benchmark. |
| Databáze: | OpenAIRE |
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