Farmer and Seasons Algorithm (FSA): A Parameter-Free Seasonal Metaheuristic for Global Optimization
International journal of intelligent engineering and systems · 2025
This paper introduces a novel metaheuristic algorithm called the Farmer and Seasons Algorithm (FSA), inspired by the adaptive behaviours of farmers in response to seasonal changes in nature.FSA simulates the way a farmer alternates between different strategies such as cultivation, observation, harvesting, and rest across varying environmental conditions, effectively modelling a dynamic and cyclic balance between exploration and exploitation.The algorithm requires no parameter tuning, which enhances its simplicity, generality, and ease of implementation.Each phase of the farming cycle is mathematically formulated, and the transitions between them are governed by deterministic rules that adapt based on the search process feedback.The FSA's performance is extensively evaluated on the CEC 2017 benchmark suite, which consists of 29 well-known test functions encompassing unimodal, multimodal, hybrid, and composite problem types.The proposed algorithm is compared against nine state-of-the-art metaheuristic algorithms.Empirical results show that FSA consistently outperforms competitors, achieving the best average rank in most test functions and demonstrating excellent convergence speed, solution accuracy, and robustness.These results highlight the algorithm's potential in solving complex optimization problems.Future directions include applying FSA to constrained and multi-objective optimization, extending its theoretical analysis, and deploying it in real-world engineering applications such as structural design, scheduling, and renewable energy systems.