Novel global optimization method

Abstract

The invention discloses a novel global optimization method, and belongs to the technical field of information. The novel global optimization method comprises the following steps: starting with a balance optimization algorithm as a core, adopting a Lycra flight path in the exploration and development process, and preventing the algorithm from falling into a local optimal solution by utilizing a walking mode of crossing Lycra flight short-distance search and occasional long-distance walking. Meanwhile, the mathematical model and the algorithm flow of the given novel global optimization algorithmfurther ensure the balance between global search and local development in the algorithm. The algorithm is applied to benchmark test function solving to test algorithm performance, compared with a mainstream intelligent algorithm, the method can be used for effectively improving the efficiency and accuracy of solving high-dimensional single-peak and multi-peak function optimal solutions, a new thought can be provided for solving more engineering optimization problems, the convergence rate of EO is increased, the global search capability of the algorithm is also improved, and the algorithm canbe effectively prevented from falling into a local optimal solution.

Description

technical field [0001] The invention belongs to the field of information technology, and in particular relates to a novel global optimization method. Background technique [0002] The Balance Optimization Algorithm is a physics-based technique proposed by Afshin Faramarzia and Mohammad Heidarinejad in 2020, inspired by dynamic resource and library models, for estimating the equilibrium state. The algorithm is based on a dynamic mass balance of the control volume, where the mass balance equation describes the concentration of non-reactive components in the control volume in terms of various resource pool models. In the equilibrium optimization algorithm, the particles are similar to the solution, and the concentration is similar to the position of the particles in the particle optimization algorithm (PSO). The mass balance equation provides the fundamental physics for the conservation of mass governing the entry, exit, and creation of objects in volumetric processes. Schola...

AI Technical Summary

Problems solved by technology

Balanced optimization algorithms perform well when solving unimodal optimization problems, but when dealing with multimodal optimization problems, the solutions obtained by EO are not ideal

It can be found that EO has good development ability and convergence speed, but it is easy to fall into the local optimal solution, the global search ability is not strong, and the convergence is not high

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