We proposed a new metaheuristic optimization algorithm , named termite life cycle optimizer (TLCO), which is based both on the life cycle of a termite colony and the modulation of movement strategies used by many animal species in nature. Termite colonies are comprised of three distinct castes: the workers, the soldiers and the reproductive termites. Each caste undertakes a set of specific tasks that ensure the growth and survival of the colony. TLCO mimics the activities of these three castes that are implemented in a mathematical model. The model is then used to find the global optimum in classic optimization problems. First, the behaviors of the workers, soldiers and reproductive termites are used to simulate a balance between the tasks of exploration and exploitation. Second, the initial population securely records the information obtained at each iteration and transmits it to workers and soldiers at the next iteration. This process is repeated until the global optimum is found with the smallest error. Besides, a new proposed function combined with Lévy flight is used to modulate the movement of termites that increases its flexibility. Thus, TLCO can cover both long distances during the first iterations to improve the convergence rate and shorter distances during the last iterations to enhance the level of accuracy

The Matlab source codes of TLCO optimized algorithm is included

Hoang Le-Minh

Thanh Sang-To

Guy Theraulaz

Magd Abdel Wahab

Thanh Cuong-Le

Minh, Hoang-Le, Thanh Sang-To, Guy Theraulaz, Magd Abdel Wahab, and Thanh Cuong-Le. "Termite life cycle optimizer." Expert Systems with Applications 213 (2023): 119211. https://doi.org/10.1016/j.eswa.2022.119211