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

• Published in: Expert systems with applications Vol. 161; p. 113702
• Main Authors: Askari, Qamar, Saeed, Mehreen, Younas, Irfan
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.12.2020; Elsevier BV
• Subjects: Algorithms; Benchmarks; Corporate hierarchy based optimization; Corporate structure; Data structures; Global optimization; Global optimization algorithm; Mechanical engineering; Nature-inspired meta-heuristic; Optimization; Rank tests; Social optimization algorithm; Source code; Nature-inspired meta-heuristic; Social optimization algorithm; Corporate hierarchy based optimization; Global optimization algorithm

•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 se...