Falco peregrinus optimization algorithm: A novel biomimetic metaheuristic algorithm for engineering applications
Liming Wei, Heng Zhong · Energy Reports · 2026
To address the limitation that existing combined cooling, heating, and power energy systems often consider either system investment costs or environmental pollution in isolation—thereby affecting overall system optimization—this paper investigates the optimal dispatch of CCHP systems. We construct a tri-objective optimization model that simultaneously minimizes renewable energy costs, CCHP system overall costs, and end-user energy purchase costs. A comprehensive CCHP system optimization model incorporating gas turbines, gas boilers, electric refrigeration units, and their associated operational constraints is established.This paper innovatively proposes the Falco peregrinus Optimization Algorithm（FPO）,a biologically-inspired swarm intelligence approach based on the living habits and predation strategies of Falco peregrinus. First, the FPO algorithm is benchmarked against five other intelligent algorithms using 15 CEC2005 standard test functions. Second, the single-objective FPO is extended to a Multi-Objective Falco peregrinus Optimization Algorithm (MOFPO). Third, the MOFPO is applied to the CCHP system optimization model and compared with the MOPSO,MOGWO,NSGA-Ⅱalgorithm. Simulation results indicate that MOFPO outperforms the other three algorithms in terms of convergence accuracy, convergence speed and stability.The experimental results conclusively demonstrate that the Falco peregrinus Optimization Algorithm effectively balances system economic efficiency and environmental protection while simultaneously reducing user electricity costs and ensuring smoother system operation. This methodology provides a foundational basis for subsequent energy supply system planning and is particularly well-suited for practical engineering applications.