Abstract
In this paper a new meta-heuristic algorithm is introduced. This optimization algorithm is inspired by the very popular tool among the technical traders in the stock market called the Fibonacci Indicator. The Fibonacci Indicator uses to predict possible local maximum and minimum prices, and periods in which the price of a stock will experience a significant amount of movement. The proposed Fibonacci Indicator algorithm is validated on several Benchmark functions up to 100 dimensions to have a comparison to algorithms such as DE extensions, PSO extensions, ABC, ABC-PS, CS, MCS and GSA in the ability of convergence and finding the global optimum in different research areas. Finally two engineering design problems are used to show the performance of the algorithm. Application of the proposed Fibonacci Indicator Algorithm in a wide set of benchmark functions has asserted its capability to deal with difficult optimization problems.
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