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Jun 13, 2024 · The GNDO algorithm, previously known for its effectiveness in single-objective optimization, has been enhanced with two key features for multi-objective optimization. The first is the addition of an archival mechanism to store non-dominated Pareto optimal solutions, ensuring a detailed record of the best outcomes.

Nov 15, 2020 · In order to test the performance of GNDO, GNDO is used for parameter extraction of three photovoltaic models. Experimental results show GNDO outperforms the compared algorithms in terms of efficiency and accuracy.

Nov 3, 2021 · This is the source code of a new metaheuristic method called generalized normal distribution optimization algorithm (GNDO). Unlike most of the reported metaheuristic methods, GNDO only needs the essential population size and terminal condition (e.g. the maximum number of function evaluations or the maximum number of iterations) for optimization.

Apr 12, 2022 · To improve the performance of GNDO for solving complex optimization problems, this work presents a new variant of GNDO, which can be called elite-driven generalized normal distribution optimization (EDGNDO).

May 26, 2022 · Generalized normal distribution optimization (GNDO) represents a newly developed optimization that confirmed its outperformance in comparison with well-known optimization algorithms on parameter extraction for photovoltaic models.

The newly proposed Generalized Normal Distribution Optimization (GNDO) algorithm is used to design the truss structures with optimal weight.

Sep 28, 2023 · This article uses a recent meta-heuristic approach named the generalized normal distribution optimization (GNDO) algorithm to achieve near-optimal solutions. The efficacy of the proposed GNDO algorithm is validated through experimentation on three distinct test power system networks: one with three thermal units, the second one with six thermal ...

May 8, 2024 · GNDO features a straightforward framework, with its information sharing mechanisms comprising local exploitation and global exploration. Exploitation leverages a generalized normal distribution model, steered by the present average and optimal positions.

This is the source code of a new metaheuristic method called generalized normal distribution optimization algorithm (GNDO). Unlike most of the reported metaheuristic methods, GNDO only needs the essential population size and terminal condition (e.g. the maximum number of function evaluations or the maximum number of iterations) for optimization.