Hybridizing Whale Optimization Algorithm With Particle Swarm Optimization for Scheduling a Dual-Command Storage/Retrieval Machine

Whale optimization algorithm (WOA) and particle swarm (PSO) have been used individually usually. However, a separate use of them has limitation. Hybridizing WOA with PSO is expected to evolve solutions better due the cooperation between whales seabirds. Developing such kind model focus this research. A framework further proposed best utilize hybridizations for developing simulation-based approaches. The advantage integrating metaheuristic, simulation, seamlessly. It can waive rigorous labor-intensive procedure required traditional simulation. In research, approaches are deal dual-command block scheduling problem manufacturing firm’s storage/retrieval (S/R) machine in an automated system. S/R mainly store/retrieve stock-keeping units Three approaches, Hybrid1 (WOA+PSO), Hybrid2 Hybrid3 developed. To investigate their effectiveness, experiments conducted compare base models, PSO, as well genetic (GA) PWOA. PWOA abbreviation hybridization previous study. experimental results show that (WOA+PSO) outperforms WOA, PWOA, GA. uses techniques hybridization, Neighborhood heuristic, adaptive movements empower most.