Optimization and inventory management under stochastic demand using metaheuristic algorithm.

ABSTRACT: This study considers multi-period inventory systems for optimizing profit and storage space under stochastic demand. A nonlinear programming model based on random demand is proposed to simulate the inventory operation. The effective inventory management system is realized using a multi-objective grey wolf optimization (MOGWO) method, reducing storage space while maximizing profit. Numerical outcomes are used to confirm the efficacy of the optimal solutions. The numerical analysis and tests for multi-objective inventory optimization are performed in the four practical scenarios. The inventory model's sensitivity analysis is performed to verify the optimal solutions further. Especially the proposed approach allows businesses to optimize profits while regulating the storage space required to

SUBMITTER: Tan ND 

PROVIDER: S-EPMC10769039 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature