Open AccessDESIGN & DEVELOPMENT OF A BIG DATA ALGORITHM OPTIMIZATION TECHNIQUE FOR A SALES SIMULATION SYSTEM OF A BUSINESS ORGANISATION
Author(s) -
Prof.Dr.G.Manoj Someswar,
AUTHOR_ID,
Ganji Vivekanand,
AUTHOR_ID
Publication year - 2021
Publication title -
international journal of innovative research in advanced engineering
Language(s) - English
Resource type - Journals
ISSN - 2349-2163
DOI - 10.26562/ijirae.2021.v0805.004
Subject(s) - negotiation , computer science , work (physics) , function (biology) , industrial engineering , range (aeronautics) , unit (ring theory) , operations research , mercantilism , algorithm , economics , engineering , mathematics , mechanical engineering , law , biology , mathematics education , market economy , evolutionary biology , aerospace engineering , political science
When sales representatives and customers negotiate, it should be confirmed that the ultimate deals can render a high enough professional t for the mercantilism company. Massive corporations have completely different strategies of doing this, one amongst that is to run sales simulations. Such simulation systems typically have to be compelled to perform complicated calculations over massive amounts of information that successively needs economical models and algorithms. This research paper intends to judge whether or not it's potential to optimize Associate in Nursing extend an existing sales system known as per centum, that is presently laid low with intolerably high running times in its simulation method. this can be done through analysis of this implementation, followed by improvement of its models and development of economical algorithms. The performance of those optimized and extended models area unit compared to the present one so as to judge their improvement. The conclusion of this research work is that the simulation method in per centum will so be optimized and extended. The optimized models function as a symptom of thought that shows that results just like the first systems are often calculated inside < 1 Chronicles of the first time period for the most important range of shoppers.