How long should offspring lifespan be in order to obtain a proper exploration?

The time an offspring should live and remain into the population in order to evolve and mature is a crucial factor of the performance of population-based algorithms both in the search for global optima, and in escaping from the local optima. Offsprings lifespan influences a correct exploration of the search space, and a fruitful exploiting of the knowledge learned. In this research work we present an experimental study on an immunological-inspired heuristic, called OPT-IA, with the aim to understand how long must the lifespan of each clone be to properly explore the solution space. Eleven different types of age assignment have been considered and studied, for an overall of 924 experiments, with the main goal to determine the best one, as well as an efficiency ranking among all the age assignments. This research work represents a first step towards the verification if the top 4 age assignments in the obtained ranking are still valid and suitable on other discrete and continuous domains, i.e. they continue to be the top 4 even if in different order.