Comparison Analysis Of PSO And SMO

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As very few control parameters are required in SMO, so it turns out to be easy to apply it in different complex optimization problems. Now-a-days, SMO is being applied in almost every field and domain of engineering optimization, function optimization, scheduling, image processing, planning, forecasting, feature selection and other real-world applications like lower order system modeling, multi-machine power system based on VSC-HVDC link, cluster based routing protocol Wireless Sensor networks, optimal power flow analysis, optimal reactive power dispatch problem, electromagnetics, diabetes classification, multilevel thresholding segmentation, placement and sizing of capacitors, antenna optimization and many others. SMO is very efficient in …show more content…

In the same year, A. A. Al-Azza, et al. [37] intended to solve electromagnetic problems like linear array antenna synthesis and patch antenna design using SMO in their paper “Spider Monkey Optimization (SMO): A novel optimization technique in Electromagnetics.” The algorithm is used to synthesize the array factor of a linear antenna array and to optimally design a coaxial feeding patch antenna for wireless applications. It was discovered that SMO was equipped to get the best arrangements with few number of trials.

In 2016, S.S. Pal, et al. [38] in the paper titled “Multi-level Thresholding Segmentation Approach Based on Spider Monkey Optimization Algorithm” introduced SMO for histogram based bi-level and multi-level segmentation of grey scale images. SMO has likewise been utilized to maximize Kapur’s and Otsu’s objective function. Results delineated that the new segmentation method is able to improve results in terms of optimum threshold values and CPU time when compared to other nature inspired algorithms.

T. Gui in 2016 [39] studied the mechanism of SMO in the field of WSNs in the paper “A Novel Cluster-based Routing Protocol Wireless Sensor Networks using Spider Monkey Optimization.” The study additionally showed the change in traditional routing protocols in term of low-energy consumption and system quality of the network. SMO-C protocol suggested in the paper worked for Wireless sensor networks to minimize global energy consumption.

In the same year, H. Wu,

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