Multi-Item Lot Sizing Optimization Involving Transportation Cost and Stochastic Demand with Aquila Algorithm

Inventory management is becoming increasingly important in an era of dynamic industrial growth. The multi-item lot sizing inventory model plays a crucial role in the ordering of raw materials when transportation costs and stochastic demand are present. This study proposes a model for multi-item inventory lot sizing that takes transportation costs and stochastic demand into account. The Aquila Algorithm is proposed as a potential solution to the issue. The results indicate that the Aquila Algorithm can produce a lower total cost than the heuristic method and the same solution as the complete enumeration procedure, Water Cycle and Whale Optimization Algorithm (WCWOA), and the Genetic Algorithm (GA).