An implementation of a distributed artificial intelligence architecture to the integrated production management

Bravo, César; Castro, José Lisandro Aguilar; Saputelli, Luigi; Ríos, Addison; Aguilar-Martín, J.; Rivas, Francklin

doi:10.1016/j.jngse.2011.08.002

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…However, he identifies that the solutions are hard for the ordinary decision-makers to follow aptly. Bravo et al, 2011) takes a different approach in the selection of articles and objectively retrieves 77 published articles from five different databases published between the years 1994 all through to 2014 and reviews the status of the application of the seven identified artificial intelligence systems in the business market and more specifically, how this could be adapted in both the textile and in the apparel industries. Bravo et al (2011) identify that the gap between the artificial intelligence and business simulation models could have been caused by unbalanced risks, which hinders research-directed development in the industry.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Bravo et al, 2011) takes a different approach in the selection of articles and objectively retrieves 77 published articles from five different databases published between the years 1994 all through to 2014 and reviews the status of the application of the seven identified artificial intelligence systems in the business market and more specifically, how this could be adapted in both the textile and in the apparel industries. Bravo et al (2011) identify that the gap between the artificial intelligence and business simulation models could have been caused by unbalanced risks, which hinders research-directed development in the industry. While the articles reviewed in this study were taken out objectively, it is important to note that machine learning algorithms of the AI techniques were listed out of seven techniques and was done so in a subjective way.…”

Section: Literature Reviewmentioning

confidence: 99%

“…While the articles reviewed in this study were taken out objectively, it is important to note that machine learning algorithms of the AI techniques were listed out of seven techniques and was done so in a subjective way. Besides this, Bravo et al (2011) only looked at the textile and the apparel industry in supply chain management, which thus reflected only a partial representation of the total business industry.…”

Section: Literature Reviewmentioning

confidence: 99%

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Artificial Intelligence in Business Simulation Analysis

Arshad¹

2020

EJT

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Purpose: Research on business simulation and machine learning has attracted immense interest in the last few years. The aim of this study was to provide a comprehensive view of machine learning in business simulation. To review the use of artificial intelligence in business simulation analysis. A review of the literature, however, shows little systematic reviews on the application of machine learning techniques to business simulation, yet systematic reviews have gained prominence in the academic jargon. Methodology: Thus, this study does reviews systematically a total of 123 shortlisted articles that focus on the machine learning techniques in the business simulation process. Findings: There are immense algorithms of machine learning which can be used in a business simulation, although this study was able to review ten machine learning algorithms in the business simulation process. As a whole, the machine learning algorithms have been deployed to yield lead-time production in the industry. In inventory and storage, machine learning has been applied to improve efficiency in identifying inventory patterns that would have never been revealed and thus saves on costs. Future direction also discussed.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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