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Lion Pride Optimizer: An Optimization Algorithm Inspired By Lion Pride Behavior

Bo Wang, Xiaoping Jin, B. Cheng
Published 2012 · Mathematics, Computer Science
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In this paper, we report a novel optimization algorithm, lion pride optimizer (LPO), which is inspired by lion pride behavior. The framework is mainly based on lion prides’ evolution process and group living theory. In a lion pride, brutal competition of individuals happens among male lions both within and among prides; on the other hand, each member plays an important role in the persistence of a lion pride. Based on this framework, concepts from lion prides behavior, e.g., the strongest males occupy nearly all mating resources, and if a new cohort of males is able to take over a pride, they will seek to kill young cubs sired by their predecessors, are employed metaphorically to design optimum searching strategies for solving continuous optimization problems. From the studies of the algorithm property, it is found that the LPO algorithm is not sensitive to most parameters, which shows the robustness of the algorithm and the parameters are not problemdependent. Central tendency of the algorithm is not found. It is found that the pride update strategy and brutal competition of individuals are two main factors that contribute to the performance of LPO. According to the test results on 23 famous benchmark functions, the LPO algorithm has better performance than the other seven state-of-the-art algorithms on both unimodal and multimodal benchmark functions; in the test of high-dimensional multimodal problems, LPO outperforms the other five algorithms on all benchmark functions.
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