Solution Space Diversity Management in a Meta-hyperheuristic Framework

Abstract

This paper investigates various strategies for the management of solution space diversity within the context of a meta-hyper heuristic algorithm. The adaptive local search meta-hyper heuristic (ALSHH), which adaptively applies a local search algorithm when the population diversity strays outside a predetermined solution space diversity profile, is proposed. ALSHH was shown to compare favourably with algorithms making use of local search and diversity maintenance strategies applied at constant intervals throughout the optimization run. Good performance is also demonstrated with respect to two other popular multi-method algorithms.