Challenge #213: Optimized Flower Arrangements

[Charity_K_Wilson]

This was HARD!

I have used the Monte Carlo simulation side before, but I haven't used the optimization side.  Now I'm wondering what business problems might fit into this algorithm.

[daiphuongngo]

Spoiler

 

[Marcel_PwC]

I agree there is kind of error in the solution - using Solver "Glpk" results in 417 flowers (agreed, max possible number) but tool decided to go with 57 Red Roses (2.30$) and 40 White Daisies (2.25$), so not the cheapest solution - probably because switching to White Daisy doesn't increase the number of total flowers. However changing Solver to "Symphony" correct this one matter. Good for Symphony!

[RWvanLeeuwen]

prepping for the expert exam and retaking this challenge

Spoiler

I now see the differences between algorithms

[olga_strubbe]

This was a neat challenge.  It gave me an opportunity to learn about the Optimization tool, which was quite neat. 

In my approach I used both linear (LP) and mixed integer linear (MLP) programming to solve the challenge using a matrix input mode.

[lynnesonneyrsm]

yay no more excel!

[Erin]

Solved using field mapping

Spoiler

This video from the Data Coach helped: https://youtu.be/og4EwRcf1iU?si=bL1XI5WJHze7sMBP 

[HardikJani]

This kept me up at night. But helped learn an amazing tool. I used the specify model as matrices mode to maximize. Fun tool and fun challenge.

[JAKupchik]

What an illustrative example of the Optimizer Tool.  Attached!  :-)  JAK

[JoshuaM]

Flower arrangement Optimized!

Alteryx workflow :

Spoiler

Explanation :

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O anchor : Consists of the variables (Flowers), Coefficient or what we are maximizing (Number of Flowers), Bounds (ub & lb - respective flower constraints), & Type (I for Integer since flowers have to be an actual number).

A anchor : Dense matrix where our variables are rows - Our variable, flowers, represents each unique flower type. The associated constraint is displayed under budget. This represents the price we would pay for each flower.

B anchor : Define the direction of each constraint. The instructions provide us with the information needed here. Since we have a budget of 950 (right hand side : rhs) we need to ensure the direction is less than or equal to that value.

S output anchor : Lastly , we can interpret the results. The objective relates back to our budget. We can see that we have achieved a value under the total budget. The values associated under name (flowers) represent the total number of flowers. Said differently, this combination of flowers would achieve an objective value under our budget.