A Novel Parameter Optimization Metaheuristic: Human Habitation Behavior Based Optimization
Divya Jain, Mithlesh Arya, Varun Malik, Shubhranshu Vikram Singh · 2022
Parameters have great impact on the performance of an optimization algorithm. This paper concerns parameter tuning for metaheuristics which are stochastic optimization algorithms. A novel, fast, and very simple population-based metaheuristic namely Human Habitation Behavior-Based optimization (HHBO) is proposed in order to tune parameters of the metaheuristics used for the weight and bias optimization problem in feed-forward neural networks. The proposed algorithm is compared with other state-of-art algorithms, and results and analysis are presented. The results show the merits of HHBO for parameter tuning in comparison of other state-of-art algorithms.