Can new optimization algorithms be designed to work infinitely to get the best results, they search the entire search area in a spherical manner and are concerned with all static and dynamic particles and possess all physical and topological properties to achieve the best possible solution?
Dear Abbas Thajeel Alsahlanee, on the basis of Bellmann's Optimality Principle, you can develop various recursive algorithms yourself to solve optimization problems. When using Bellmann's Optimality Principle, one speaks of Dynammig Programming (DP). The idea of DP is very well suited for the development of various recursive optimization algorithms for signal processing. See my little literature list.
At the beginning of the 1970s, in order to be able to use DP to solve economic problems (without a computer!), I introduced simple graphic models. See the figures under: https://www.researchgate.net/publication/312033832_Dynamic_Programming
Best regards and good luck
Anatol Badach
Andrey Valerievich Kopylov, Olga Krasotkina, Oleksandr Pryimak, Vadim Mottl: A Signal Processing Algorithm Based on Parametric Dynamic Programming; DOI: 10.1007/978-3-642-13681-8_33 https://www.researchgate.net/publication/221156819
EDWARD ANGEL: From Dynamic Programming to Fast Transforms; JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS 119, 82-89 (1986) https://core.ac.uk/download/pdf/81109641.pdf
Rutger-Jan Lange: Bellman filtering for state-space models https://papers.tinbergen.nl/20052.pdf
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