This paper presents a literature review about Particle Swarm Optimization (PSO), Firework, Firefly, Clonal Selection, and Cuckoo Search algorithms, which are among the most common natural-inspired optimization algorithms. These algorithms were tried on different benchmark functions. The obtained results analyzed, performance was compared. showed that PSO Firefly provided best in studied cases.

The Traveling Salesman Problem is a standard test-bed for algorithmic ideas. Currently, there exists a large number of nature-inspired algorithms for the TSP and for some of these approaches very good performance is reported. In particular, the best performing approaches combine solution modification or construction with the subsequent application of a fast and effective local search algorithm....

Multimodal therapy has been recognized as a powerful platform for the precise treatment of cancer. However, reported multimodal therapeutic systems often involve sophisticated components and tedious fabrication procedures. As such, developing nature-inspired easily-obtainable theranostic agents cancer remains challenging. In this work, we propose nanothylakoids agent both in vitro vivo. Nanothy...

Nature-inspired algorithms are recently being appreciated for solving complex optimization and engineering problems. Black hole algorithm is one of the recent nature-inspired algorithms that have obtained inspiration from black hole theory of universe. In this paper, four formulations of multi-objective black hole algorithm have been developed by using combination of weighted objectives, use of...

Irrelevant, noisy and high dimensional data, containing large number of features, degrades the performance of data mining and machine learning tasks. One of the methods used in data mining to reduce the dimensionality of data is feature selection. Feature selection methods select a subset of features that represents original features in problem domain with high accuracy. Various methods have be...