I ran a Linear Regression on my data on a hotel reservation to find out the following model fit in R:

Sales = 170.2 + 3.6Days_left_to_checkIn + 7.6Revenue - 9.6Room_Rate -7.67cancellation_price + 4.8Number_of_cancelled_Room -8.9Online_reputation_of_Hotel

after this, I used Optimized function to optimize the equation for maximum revenue (Revenue = Room_Rate* Sales)

after substituting all the values of variables I got this equation

f=-9.6Room_Rate^2 + Room_Rate253.56

Optimize(f, lwr=10, upr=524)

What is the next step to calculate Room_Rate to maximize the revenue (revenue = Room_Rate * Sales) Is there any better way to optimize the function of demand

I ran linear regression on my hotel reservation data and obtained the following model fit in R:

Sales = 170.2 + 3.6Days_left_to_checkIn + 7.6Revenue - 9.6Room_Rate -7.67cancellation_price + 4.8Number_of_cancelled_Room -8.9Online_reputation_of_Hotel

After this, I used the Optimize function to optimize the equation for maximum revenue (Revenue = Room_Rate* Sales)

after substituting all the values of variables I got this equation

f=-9.6Room_Rate^2 + Room_Rate253.56

Optimize(f, lwr=10, upr=524)

What is the next step to calculate Room_Rate to maximize the revenue (revenue = Room_Rate * Sales)? Is there any better way to optimize the function of demand?