Red Panda Optimization Algorithm: An Effective Bio-Inspired Metaheuristic Algorithm for Solving Engineering Optimization Problems

This paper presents a new bio-inspired metaheuristic algorithm called Red Panda Optimization (RPO) that imitates the natural behaviors of red pandas in nature. The main design idea RPO is derived from two characteristic pandas: (i) foraging strategy, and (ii) climbing trees to rest. proposed approach mathematically modeled phases exploration based on simulation pandas’ strategy exploitation movement trees. advantage there no control parameter its mathematical modeling, for this reason, it does not need adjustment process. performance evaluated fifty-two standard benchmark functions including unimodal, high-dimensional multimodal, fixed-dimensional multimodal types as well CEC 2017 test suite. optimization results obtained by are compared with twelve well-known algorithms. show RPO, maintaining balance between exploitation, effective solving problems superior over competitor Based analysis results, has provided more successful algorithms 100% unimodal functions, 86.2% suite functions. Also, statistical Wilcoxon rank sum shows superiority competition significant point view. In addition, implementing four engineering confirms ability handle real-world applications.