Quantum-inspired African vultures optimization algorithm with elite mutation strategy for production scheduling problems

Abstract The Production Scheduling (PS) problem is a challenging task that involves assigning manufacturing resources to jobs while ensuring all constraints are satisfied. key difficulty in PS determining the appropriate order of operations. In this study, we propose novel optimization algorithm called Quantum-inspired African Vultures Optimization Algorithm with an Elite Mutation Strategy (QEMAVOA) address issue. QEMAVOA enhanced version Vulture (AVOA) incorporates three new improvement strategies. Firstly, enhance QEMAVOA's diversification ability, population diversity enriched by introduction Quantum Double-Chain Encoding (QDCE) initialization phase QEMAVOA. Secondly, implementation Rotating Gate (QRG) will balance and exploitation capabilities, leading vulture better solution. Finally, purpose improving exploitability QEMAVOA, (EM) strategy introduced. To evaluate performance apply it two benchmark scheduling problems: Flexible Job Shop (FJSP) Parallel Machine (PMS). results compared those existing algorithms literature. test reveal surpasses comparison accuracy, stability, speed convergence.