In this paper, a novel nature-inspired optimization algorithm, hazelnut tree search (HST) is proposed for solving numerical and engineering optimization problems. HST is a multi-agent algorithm that simulates the search process for finding the best hazelnut tree in a forest. The algorithm is composed of three main actuators: growth, fruit scattering, and root spreading. In the growth phase, trees compete with each other on shared resources to grow up and improve their fitness. In the fruit scattering phase, HTS performs exploration by simulating the movement of hazelnuts around the forest with the help of animals and rodents. In the root spreading, HTS performs exploitation by modeling the root spreading mechanism of trees around themselves. The performance of the proposed algorithm is evaluated on multi-variable unconstraint numerical optimization benchmarks and constraint engineering problems. Comparing the proposed algorithm with a few other optimization algorithms shows the superiority of the HTS in terms of problem-solving success and finding the global optimum on most benchmark problems.
