Optimization and inventory management under stochastic demand using metaheuristic algorithm

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 gre...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:PloS one Ročník 19; číslo 1; s. e0286433
Hlavní autori: Tan, Nguyen Duy, Kim, Hwan-Seong, Long, Le Ngoc Bao, Nguyen, Duy Anh, You, Sam-Sang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States Public Library of Science 05.01.2024
Public Library of Science (PLoS)
Predmet:
Algorithms
Analysis
Decision making
Demand
Evaluation
Forecasts and trends
Genetic algorithms
Heuristic methods
Hydrologic cycle
Information management
Internet of Things
Inventory
Inventory control
Inventory management
Logistics
Mathematical models
Mathematical optimization
Methods
Multiple objective analysis
Nonlinear programming
Numerical analysis
Optimization
Optimization algorithms
Sensitivity analysis
Supply chain management
Supply chains
South Korea
ISSN:1932-6203, 1932-6203
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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 operate in inventory management. The supply chain performance can be significantly enhanced using inventory management strategies and inventory management practices. Finally, the novel decision-making strategy can offer new insights into effectively managing digital supply chain networks against market volatility.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0286433