EconPapers    
Economics at your fingertips  
 

Optimization in solving inventory control problem using nature inspired Emperor Penguins Colony algorithm

Sasan Harifi (), Madjid Khalilian, Javad Mohammadzadeh and Sadoullah Ebrahimnejad
Additional contact information
Sasan Harifi: Islamic Azad University
Madjid Khalilian: Islamic Azad University
Javad Mohammadzadeh: Islamic Azad University
Sadoullah Ebrahimnejad: Islamic Azad University

Journal of Intelligent Manufacturing, 2021, vol. 32, issue 5, No 8, 1375 pages

Abstract: Abstract In the present day markets, it is essential for organizations that manage their supply chain efficiency to sustain their market share and improve profitability. Optimized inventory control is an integral part of supply chain management. In inventory control problems, determining the ordering times and the order quantities of products are the two strategic decisions either to minimize total costs or to maximize total profits. This paper presents three models of inventory control problems. These three models are deterministic single-product, deterministic multi-product, and stochastic single-product. Due to the high computational complexity, the presented models are solved using the Emperor Penguins Colony (EPC) algorithm as a metaheuristic algorithm and a soft computing method. EPC is a newly published metaheuristic algorithm, which has not yet been employed to solve the inventory control problem. The results of applying the proposed algorithm on the models are compared with the results obtained by nine state-of-the-art and popular metaheuristic algorithms. To justify the proposed EPC, both cost and runtime criteria are considered. To find significant differences between the results obtained by algorithms, statistical analysis is used. The results show that the proposed algorithm for the presented models of inventory control has better solutions, lower cost, and less CPU consumption than other algorithms.

Keywords: Inventory control problem; Metaheuristic algorithm; Nature-inspired; Emperor penguins colony algorithm; Deterministic single-product model; Deterministic multi-product model; Stochastic single-product model (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10845-020-01616-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:32:y:2021:i:5:d:10.1007_s10845-020-01616-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-020-01616-8

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joinma:v:32:y:2021:i:5:d:10.1007_s10845-020-01616-8