Table 1.
Notations of inventory parameters and variables.
Fig 1.
Inventory level of an item with multiple periods (discrete demand).
Fig 2.
Inventory level of an item with multiple periods (continuous demand).
Table 2.
Pseudocode of Monte Carlo in inventory simulation.
Fig 3.
Implementation of positions updating in grey wolf optimizer.
Fig 4.
Flowchart of the basic MOGWO algorithm.
Table 3.
Pseudocode of multi-objective optimization.
Table 4.
Initial parameters of inventory items.
Fig 5.
Random demand for four items in 365 days.
Fig 6.
Convergence analysis for the optimal solutions in the search space (Item 1).
Fig 7.
Convergence analysis for the optimal solutions in search space (Item 2).
Fig 8.
Convergence analysis for optimal solutions in the search space (Item 3).
Fig 9.
Convergence analysis for optimal solutions in the search space (Item 4).
Fig 10.
Pareto frontier of the optimization process.
Fig 11.
Optimal solution from a set of solutions (μ = λ = 0.5).
Table 5.
Sensitive analysis for inventory items (μ = λ = 0.5).