Cendrawasih Bird Optimization Algorithm : A nature-inspired metaheuristic

Widi Aribowo (Universitas Negeri Surabaya)
Laith Abualigah (Computer Science Department, Al al-Bayt University, Mafraq 25113, Jordan)
Diego Oliva (Depto. de Ingeniería Electro-Fotónica, Universidad de Guadalajara, CUCEI, Guadalajara, México)
Abeer Aljohani (Department of Computer Science, Applied College, Taibah University, Madinah, Saudi Arabia)
Aliyu Sabo (Department of Electrical and Electronic Engineering, Nigerian Defence Academy, Kaduna, Nigeria)

Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 14, No 2: June 2026

This study proposes a new metaheuristic algorithm named Cendrawasih Bird Optimization Algorithm (COA), inspired by the natural behavior of Cendrawasih birds—an endemic species of Indonesia. COA mimics the main behavior of the birds, namely exploration and exploitation, to create a balance between global exploration and local exploitation capabilities in solving various optimization problems. This algorithm is mathematically modeled and evaluated using 23 benchmark functions from CEC 2017, and its performance is compared against eight state-of-the-art metaheuristic algorithms. The results of numerical experiments, convergence analysis, and statistical tests show that COA has competitive performance, especially in terms of stability and consistency on unimodal and multimodal functions. Overall, COA is proven to be a reliable, robust, and efficient optimization tool with broad application potential in various engineering and scientific fields.