Enhancing Rider Optimization Algorithm with Chaos Theory for Multi-dimensional Optimization in Engineering Design

This work proposes H-ROACM, a hybrid optimization technique that combines the Rider Optimization Algorithm (ROA) with Chaos theory, to solve multi-dimensional engineering design optimization problems. The Rider Optimization Algorithm, inspired by racing dynamics, offers a novel optimization perspective but struggles with convergence speed and flexibility. Chaos theory enhances algorithm exploration and performance. The H-ROACM algorithm, which combines chaos-driven dynamics with the Rider Optimization Algorithm, is developed and implemented. Chaos theory adds unpredictability and flexibility to optimization. Engineering design difficulties from response surface benchmarks to industrial design challenges are examined with the method. Many performance indicators are used to evaluate H-ROACM. Objective function values are assessed for Mean, Standard Deviation, Maximum, and Minimum to evaluate algorithm convergence stability and solution quality. The efficiency of chaos-infused optimization is also assessed by computational time. Initial results show that H-ROACM exceeds ROA in convergence speed, solution quality, and adaptability to complicated engineering design environments. Chaos theory improves exploration, helping the algorithm explore multi-dimensional solution spaces. The technique improves Mean performance, reduces Standard Deviation, and adapts to shifting optimization landscapes. Application of H-ROACM to engineering design issues includes response surface benchmarks and real-world challenges. This technique is ideal for optimizing complicated engineering design systems due to its versatility. In conclusion, hybridizing the Rider Optimization Algorithm with Chaos theory may improve multi-dimensional engineering design optimization. H-ROACM's competitive dynamics and chaotic exploration boost convergence efficiency and solution quality. This study adds to the understanding of chaos theory in optimization algorithms and suggests its use in engineering design problems.