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Retail
Inventories Optimization- forecast optimal stock level that can meet
customer needs, reduce waste and lessen storage; predict the demand based on
previous buyers' activity.
Input data: characteristics of previous buyers' activity, operating
parameters, season, stock, and budgets.
Scheduling
Optimization- predict demand to schedule buses, airplanes, and
elevators.
Input data: season, day-of-week, hour of the day, special events in the
city/area, weather, etc.
Managerial
decision making- select the best decision option using the
classification capabilities of neural network.
Input data: initial problem parameters and final outcome.
Cash flow
forecasting- maximize the use of resources with more accurate cash
flow forecasts.
Input data: accounts payable, accounts receivable, sales forecasts,
budgets, capital expenditures, stock, season, operating data, etc
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