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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2019 Vol.9(2): 168-173 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.2.782

Innovative Inventory Pooling System Based on Computing and Optimization Techniques

Lilawadi Phatanarajata, Sukree Sinthupinyo, Achara Chandrachai, and Thira Chavarnakul
Abstract—Monte Carlo Simulation method is a famous and well known technique, which can be effectively used to solve inventory management problems in many industries. Thus, this study combines not only computing but also optimization techniques to provide the most optimal solution for solving inventory problems of sport retailers in Thailand. The purpose of this study is to determine the optimal system service fee for Innovative Inventory Pooling System (IIPS) by maximizing the increment of system service income and total profit. The simulation model has represented the inventory levels of sports retailers comparing between the traditional models and pooling model. Employing Monte Carlo Simulation (MCS), the simulation model establishes the opportunity for reducing cost of lost sales, and creating the profit and system service income. Therefore, three specific factors are discussed in this study. A simple equation to find the optimal system service fee for IIPS is definitely developed. Finally, the result will be presented to demonstrate the maximized system service fee and it will also use the results obtained for designing and developing the system in order to help create the maximum sustainable usability in the future.

Index Terms—Monte Carlo Simulation, optimization technique, inventory management, inventory pooling.

L. Phatanarajata is with the School of Technopreneurship and Innovation Management, Chulalongkorn University, 254 Phayathai Rd., Phatumwan Bangkok, 10330 Thailand (e-mail: lilawadi.ph@student.chula.ac.th).
S. Sinthupinyo is with the Department of Computer Engineering, Chulalongkorn University, 254 Phayathai Rd., Phatumwan Bangkok, 10330 Thailand (e-mail: sukree.s@chula.ac.th).
A. Chandrachai and T. Chavarnakul are with the Faculty of Commerce and Accountancy, Chulalongkorn University, 254 Phayathai Rd., Phatumwan Bangkok, 10330 Thailand (e-mail: achandrachai@gmail.com, thira@cbs.chula.ac.th).

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Cite: Lilawadi Phatanarajata, Sukree Sinthupinyo, Achara Chandrachai, and Thira Chavarnakul, "Innovative Inventory Pooling System Based on Computing and Optimization Techniques," International Journal of Machine Learning and Computing vol. 9, no. 2, pp. 168-173, 2019.

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E-mail: ijmlc@ejournal.net