A Comparative Study between the Greedy and Dynamic Technique for Better Optimization Performance


Authors : Mirza Samiulla Beg; Akhilesh A. Waoo

Volume/Issue : Volume 6 - 2021, Issue 10 - October

Google Scholar : http://bitly.ws/gu88

Scribd : https://bit.ly/3krVkTI

Greedy algorithms can be classified as blind. In a simple way, it always looks to the future and does not look back on the past. All the greed you are trying to achieve is trying to accumulate the best value in the solutions at hand, even though some of the solutions may be very useful in the future. The Dynamic (DP) system is different from greed in the way in which an improved solution is selected. As mentioned earlier, greedy people are constantly on the lookout for profits without regard for the future or the past. DP produces all possible solutions from handmade solutions, and then reevaluates and re-runs all of them to choose the best solution. In this paper, I want to tell you that a strong process gives better results than the method of greed. It can therefore be said that if we apply the dynamic techniques in the Artificial Bee Colony Algorithm, then it will give us better results. In this paper, I have shown that motivation strategies are better.

Keywords : WSN (Wireless Sensor Network), ABC (Artificial Bee Colony) Algorithm, DP (Dynamic Technique), BS (Base Station), IoT (Internet of Things).

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