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In the recent years, many heuristic optimization algorithms have been developed. A majority of these heuristic algorithms have been derived from the behavior of biological or physical systems in nature. In this paper, we propose a new optimization algorithm based on competitive behavior of animal groups. In the proposed algorithm, the whole population is divided into a number of groups. In each group, the best searching agent spreads its children in its owned territory. Any group which is not able to find rich resources will be eliminated form competition. The competition gradually results in an increase in population of wealthy group which gives a fast convergence to proposed optimization algorithm. In the following, after a detailed explanation of the algorithm and pseudo code, we compare it to other existing algorithms, including genetics and particle swarm optimizations. Applying the proposed algorithm on various benchmark cost functions, shows faster and superior results compared to other optimization algorithms.

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Abstract-This paper presents a new rectangle-slot antenna for ultra wideband applications with 3.5/5.5 GHz dual stop-band characteristics. The antenna contains a simple square radiating patch and a rectangle-slot ground plane, which provides a wide bandwidth from 2.6 GHz up to 14.1 GHz. In order to obtain dual stop-band properties at 3.5 and 5.5 GHz, a rectangular-shaped slot is etched off the ground plane, and a strip line ended up a shorting pin is applied, respectively. The antenna is simple in configuration and has a compact dimension of 20×22 mm 2 . The proposed antenna is designed, simulated and fabricated. The measured results exhibit a acceptable agreement with the simulated data. The antenna provides nearly omnidirectional radiation patterns, relatively flat gain over the entire UWB frequency excluding the two stop bands.