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On the Development of a Novel Smell Agent Optimization (SAO) for Optimization Problems

A. T. Salawudeen*, M. B. Mu'azu **, Y. A. Sha'aban***, E. A. Adedokun****

*-**,****Department of Computer Engineering, Ahmadu Bello University, Zaria, Nigeria.

*** Department of Electrical Engineering, University of Hafer Al-Batin, Saudi Arabia.

Periodicity:December - February'2019
DOI : https://doi.org/10.26634/jpr.5.4.15677

Abstract

This paper presents the development of a new optimization algorithm called the Smell Agent Optimization (SAO). The algorithm uses the phenomenon of smell and the intuitive trailing behavior of an agent to identify a smell source. The developed algorithm has two basic modes used in the optimization process, which are the sniffing mode and trailing mode. In the sniffing mode, the evaporation of smell molecules from a source is modeled and in the trailing mode, the movement of an agent towards the smell molecules is modeled. The performance of SOA was evaluated using 10 benchmark functions and results was compared with PSO, ABC, and GA. Simulation results showed the efficiency of the developed SAO in solving unimodal and multimodal functions.

Keywords

SAO, Smell Molecules, PSO, ABC, GA, Olfaction.

How to Cite this Article?

Salawudeen, A. T., Mu'azu, M. B., Sha'aban, Y. A., & Adedokun, E. A. (2019).On the Development of a Novel Smell Agent Optimization (SAO) For Optimization Problems. i-manager’s Journal on Pattern Recognition, 5(4), 13-26. https://doi.org/10.26634/jpr.5.4.15677

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