Heap-based optimizer inspired by corporate rank hierarchy for global optimization

Qamar Askari, Mehreen Saeed, Irfan Younas

Abstract: Highlights•Heap-based optimizer (HBO) inspired by corporate rank hierarchy (CRH) is proposed.•HBO utilizes heap to map the hierarchy and model equations for 3 CRH activities.•A parameter (γ) to escape local optima without lacking exploitation is introduced.•Exploration and exploitation are balanced through self-adaptive parameters.•Performance is evaluated on 97 benchmarks and 3 mechanical engineering problems.