The Patch-Levy-Based Bees Algorithm Applied to Dynamic Optimization Problems

The Patch-Levy-Based Bees Algorithm Applied to Dynamic Optimization Problems

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Many real-world optimization problems are actually of dynamic nature.These problems change over time in terms of the objective function, Development of sarcopenia-based nomograms predicting postoperative complications of benign liver diseases undergoing hepatectomy: A multicenter cohort study decision variables, constraints, and so forth.Therefore, it is very important to study the performance of a metaheuristic algorithm in dynamic environments to assess the robustness of the algorithm to deal with real-word problems.

In addition, it is important to adapt the existing metaheuristic algorithms to perform well in dynamic environments.This paper investigates a recently proposed version of Bees Algorithm, which is called Patch-Levy-based Bees Algorithm (PLBA), on solving dynamic problems, and adapts it to deal with such problems.The performance of the PLBA is compared with other BA versions and other state-of-the-art algorithms on a set of dynamic multimodal benchmark problems of different degrees of difficulties.

The results of the experiments show that PLBA Digital games and learning mathematics: Student, teacher and parent perspectives achieves better results than the other BA variants.The obtained results also indicate that PLBA significantly outperforms some of the other state-of-the-art algorithms and is competitive with others.