Chaotic Optimization of Tubular Column Engineering Problem with Game-Based Metaheuristics

Abstract

This paper presents new models of the Battle Royale Optimization (BRO) algorithm that are improved by integrating it with chaotic maps. The paper aims to optimize the BRO algorithm using chaotic maps, addressing the challenge of balancing exploration and exploitation, a common challenge in optimization problems. Five different chaotic maps are integrated into BRO to create Bernoulli-BRO, Cubic-BRO, Duffing-BRO, Intermittency-BRO and Liebovtech-BRO models. The chaotic BRO models developed in the study are tested on the Tubular Column Design Problem, one of the engineering problems. The results show that the Intermittency-BRO algorithm performs the best and achieves the lowest optimum costs compared to the other models. It is also observed that chaotic BRO algorithms give more consistent results with lower average cost than classical BRO. In conclusion, this study shows that chaotic maps can be successfully used in optimization problems and chaotic BRO algorithms exhibit superior performance compared to classical BRO. Especially the Intermittency-BRO algorithm gives the best results in terms of both cost and statistical data. The results of the paper emphasize that chaotic maps offer a more effective approach to optimization problems by improving the balance between the exploration and exploitation capabilities of the BRO algorithm.