Excel
| A | B | C | D | E | F | G | H |
---|-----------------|----------|--------|--------|-----------|-------------|---------|----------|---
1 | Loan | 50.000 | Year | Start | Interests | Repayment | Annuity | End |
2 | Interests p.a. | 2% | 1 | 50.000 | -1.250 | -1.750 | -3.000 | 48.250 |
3 | Annuity p.a. | 3.000 | 2 | 48.250 | -1.206 | -1.794 | -3.000 | 46.456 |
4 | Maturity | ?? | 3 | 46.456 | -1.161 | -1.839 | -3.000 | 44.618 |
5 | | | 4 | 44.618 | -1.115 | -1.885 | -3.000 | 42.733 |
| | | | | | | | |
| | | | | | | | |
21 | | | 20 | 8.094 | -202 | -2.798 | -3.000 | 5.297 |
22 | | | 21 | 5.297 | -132 | -2.868 | -3.000 | 2.429 |
23 | | | 22 | 2.429 | -61 | -2.939 | -3.000 | 0 |
The above loan of 50.000 has an interest rate of 2% and an annuity of 3.000.
In the table from C1:H23 the annual development of the remaining loan is displayed.
Based on this helper table I know that the maturity of the loan is 22 years by using the following formula in Cell B4:
B4 = COUNTA(C1:C22)
However, my question is if there is an Excel-Formula that can calculate the maturity in one cell so I do not need the helper table in C1:H23?
Excel-File
| A | B | C | D | E | F |
---|--------------|-------------------|--------|-----------------|------------|------------|-
1 | Sales | Product | | Product | Sales | |
2 | 20 | Product_A | | Product_D | 100 | Product_D |
3 | 10 | Product_A | | Product_D | 90 | |
4 | 50 | Product_A | | Product_D | 50 | |
5 | 80 | Product_B | | Product_D | 50 | |
6 | 40 | Product_C | | | | |
7 | 30 | Product_C | | | | |
8 | 100 | Product_D | | | | |
9 | 90 | Product_D | | | | |
10 | 50 | Product_D | | | | |
11 | 50 | Product_D | | | | |
12 | | | | | | |
In Column B I have list of different products with their corresponding sales in Column A.
Products can appear mutliple times in the list.
Sales numbers can be equal for multiple products.
I want to use the value in Cell F2 as Filter-Criteria to create a descending list of the products in Column D and Column E sorted by the sales in Column A.
Therefore, I tried to add the FILTER function to the formula from this question:
=INDEX(SORT(FILTER(A2:B11,A2:A11=F2,""),2,-1),SEQUENCE(COUNT(A2:A11)),{2,1})
However, with this formula I get error #VALUE.
How do I need to modify the formula to make it work?
Simply add COUNTIF() inside the SEQUENCE():
=INDEX(SORT(FILTER(A2:B11,B2:B11=F2,""),2,-1),SEQUENCE(COUNTIF(B2:B11,F2)),{2,1})
Current view on OP side:
Due to unknown reason only Column D gets filled.
I want to compose sales table for purchased and sold items to see total profit. It's easy to do when items are purchased and sold individually or as a lot. But how to handle situation when one buys collection of items and sells them one by one. For example, I buy a collection (C) of a hammer and a screwdriver and sell tools separately. If I would enter data into simple table as in the image, I would get wrong profit result.
When there are only two items, I could divide their purchase price randomly, but when there are many items and not all of them are yet sold, I can't easily see if this collection already made profit or not.
I expect correct output of profit. In this case collection cost was 10 and selling price of all collection items was 13. Thus it should show profit of 3, not loss of -7. I was thinking of adding 2 new column, like IsCollection, CollectionID. Then derive a formula, which would use either simple subtraction or would check price of a whole collection and subtract it from the sum of items that belong to that collection. Deriving such formula is another question... But maybe there is an easier way of accomplishing the same
I added a column COLLECTION to identify item who belong to a collection.
Then I used SUMIF to sum sell price for items which belong at the same collection.
Then I used IF in Profit column to use summed sell price or single sell price.
You need to define in some formula a range of cell (see below).
Problem: you can't add profit values to obtain Total profit.
I used opencalc (but it should be almost the same in Excel).
Content of
SUM_COLL (row2):
=SUMIF($A$1:$A$22;"="&A2;$D$1:$D$22)
SUM_COLL (row3):
=SUMIF($A$1:$A$22;"="&A3;$D$1:$D$22)
and so on.
Profit (row2):
=IF(A2<>"";E2-C2;D2-C2)
Profit (row3):
=IF(A3<>"";E3-C3;D3-C3)
+------------+-----------+-------------+------------+----------+--------+
| COLLECTION | Item name | Purch Price | Sell Price | SUM_COLL | Profit |
+------------+-----------+-------------+------------+----------+--------+
| | A | 1 | 1.5 | 0 | 0.5 |
+------------+-----------+-------------+------------+----------+--------+
| | B | 2 | 2.1 | 0 | 0.1 |
+------------+-----------+-------------+------------+----------+--------+
| C | C1 | 10 | 7 | 27 | 17 |
+------------+-----------+-------------+------------+----------+--------+
| C | C2 | 10 | 6 | 27 | 17 |
+------------+-----------+-------------+------------+----------+--------+
| D | D1 | 7 | 15 | 23 | 16 |
+------------+-----------+-------------+------------+----------+--------+
| | E | 8 | 12 | 0 | 4 |
+------------+-----------+-------------+------------+----------+--------+
| C | C3 | 10 | 14 | 27 | 17 |
+------------+-----------+-------------+------------+----------+--------+
| D | D2 | 7 | 8 | 23 | 16 |
+------------+-----------+-------------+------------+----------+--------+
| | | | | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+
| | | | | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+
| | | | | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+
| | | | | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+
Update:
I added two more column to make Profit summable:
COUNT_COLL (row2):
=COUNTIF($A$1:$A$22;"="&A2)
COUNT_COLL (row3):
=COUNTIF($A$1:$A$22;"="&A3)
Profit_SUMMABLE (row2)
=IF(A2<>"";(E2-C2)/G2;D2-C2)
Profit_SUMMABLE (row3)
=IF(A3<>"";(E3-C3)/G3;D3-C3)
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| COLLECTION | Item name | Purch Price | Sell Price | SUM_COLL | Profit | COUNT_COLL | Profit_SUMMABLE |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | A | 1 | 1.5 | 0 | 0.5 | 0 | 0.5 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | B | 2 | 2.1 | 0 | 0.1 | 0 | 0.1 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| C | C1 | 10 | 7 | 27 | 17 | 3 | 5.6666666667 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| C | C2 | 10 | 6 | 27 | 17 | 3 | 5.6666666667 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| D | D1 | 7 | 15 | 23 | 16 | 2 | 8 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | E | 8 | 12 | 0 | 4 | 0 | 4 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| C | C3 | 10 | 14 | 27 | 17 | 3 | 5.6666666667 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| D | D2 | 7 | 8 | 23 | 16 | 2 | 8 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | | | | 0 | 0 | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | | | | 0 | 0 | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
| | | | | 0 | 0 | 0 | 0 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
...
...
| TOTAL | | | | | 87.6 | | 37.6 |
+------------+-----------+-------------+------------+----------+--------+------------+-----------------+
Oil Blending
An oil company produces three brands of oil: Regular, Multigrade, and
Supreme. Each brand of oil is composed of one or more of four crude stocks, each having a different lubrication index. The relevant data concerning the crude stocks are as follows.
+-------------+-------------------+------------------+--------------------------+
| Crude Stock | Lubrication Index | Cost (€/barrell) | Supply per day (barrels) |
+-------------+-------------------+------------------+--------------------------+
| 1 | 20 | 7,10 | 1000 |
+-------------+-------------------+------------------+--------------------------+
| 2 | 40 | 8,50 | 1100 |
+-------------+-------------------+------------------+--------------------------+
| 3 | 30 | 7,70 | 1200 |
+-------------+-------------------+------------------+--------------------------+
| 4 | 55 | 9,00 | 1100 |
+-------------+-------------------+------------------+--------------------------+
Each brand of oil must meet a minimum standard for a lubrication index, and each brand
thus sells at a different price. The relevant data concerning the three brands of oil are as
follows.
+------------+---------------------------+---------------+--------------+
| Brand | Minimum Lubrication index | Selling price | Daily demand |
+------------+---------------------------+---------------+--------------+
| Regular | 25 | 8,50 | 2000 |
+------------+---------------------------+---------------+--------------+
| Multigrade | 35 | 9,00 | 1500 |
+------------+---------------------------+---------------+--------------+
| Supreme | 50 | 10,00 | 750 |
+------------+---------------------------+---------------+--------------+
Determine an optimal output plan for a single day, assuming that production can be either
sold or else stored at negligible cost.
The daily demand figures are subject to alternative interpretations. Investigate the
following:
(a) The daily demands represent potential sales. In other words, the model should contain demand ceilings (upper limits). What is the optimal profit?
(b) The daily demands are strict obligations. In other words, the model should contain demand constraints that are met precisely. What is the optimal profit?
(c) The daily demands represent minimum sales commitments, but all output can be sold. In other words, the model should permit production to exceed the daily commitments. What is the optimal profit?
QUESTION
I've been able to construct the following model in Excel and solve it via OpenSolver, but I'm only able to integrate the mix for the Regular Oil.
I'm trying to work my way through the book Optimization Modeling with Spreadsheets by Kenneth R. Baker but I'm stuck with this exercise. While I could transfer the logic from another blending problem I'm not sure how to construct the model for multiple blendings at once.
I modeled the problem as a minimization problem on the cost of the different crude stocks. Using the Lubrication Index data I built the constraint for the R-Lub Index as a linear constraint. So far the answer seems to be right for the Regular Oil. However using this approach I've no idea how to include even the second Multigrade Oil.
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Decision Variables | | | | | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| | C1 | C2 | C3 | C4 | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Inputs | 1000 | 0 | 1000 | 0 | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| | | | | | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Objective Function | | | | | | Total | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Cost | 7,10 € | 8,50 € | 7,70 € | 9,00 € | | 14.800,00 € | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| | | | | | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Constraints | | | | | | LHS | | RHS |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| C1 supply | 1 | | | | | 1000 | <= | 1000 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| C2 supply | | 1 | | | | 0 | <= | 1100 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| C3 supply | | | 1 | | | 1000 | <= | 1200 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| C4 supply | | | | 1 | | 0 | <= | 1100 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| R- Lub Index | -5 | 15 | 5 | 30 | | 0 | >= | 0 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| R- Output | 1 | 1 | 1 | 1 | | 2000 | = | 2000 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| | | | | | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| Blending Data | | | | | | | | |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
| R- Lub | 20 | 40 | 30 | 55 | | 25 | >= | 25 |
+--------------------+--------+--------+--------+--------+--+-------------+----+------+
Here is the model with Excel formulars:
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Decision Variables | | | | | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| | C1 | C2 | C3 | C4 | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Inputs | 1000 | 0 | 1000 | 0 | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| | | | | | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Objective Function | | | | | | Total | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Cost | 7,1 | 8,5 | 7,7 | 9 | | =SUMMENPRODUKT(B5:E5;B8:E8) | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| | | | | | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Constraints | | | | | | LHS | | RHS |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| C1 supply | 1 | | | | | =SUMMENPRODUKT($B$5:$E$5;B11:E11) | <= | 1000 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| C2 supply | | 1 | | | | =SUMMENPRODUKT($B$5:$E$5;B12:E12) | <= | 1100 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| C3 supply | | | 1 | | | =SUMMENPRODUKT($B$5:$E$5;B13:E13) | <= | 1200 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| C4 supply | | | | 1 | | =SUMMENPRODUKT($B$5:$E$5;B14:E14) | <= | 1100 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| R- Lub Index | -5 | 15 | 5 | 30 | | =SUMMENPRODUKT($B$5:$E$5;B15:E15) | >= | 0 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| R- Output | 1 | 1 | 1 | 1 | | =SUMMENPRODUKT($B$5:$E$5;B16:E16) | = | 2000 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| | | | | | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| Blending Data | | | | | | | | |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
| R- Lub | 20 | 40 | 30 | 55 | | =SUMMENPRODUKT($B$5:$E$5;B19:E19)/SUMME($B$5:$E$5) | >= | 25 |
+--------------------+------+-----+------+----+--+----------------------------------------------------+----+------+
A nudge in the right direction would be a tremendous help.
I think you want your objective to be Profit, which I would define as the sum of sales value - sum of cost.
To include all blends, develop calculations for Volume produced, Lube Index, Cost, and Value for each blend. Apply constraints for volume of stock used, volume produced, and lube index, and optimize for Profit.
I put together the model as follows ...
Columns A through D is the information you provided.
The 10's in G2:J5 are seed values for the stock volumes used in each blend. Solver will manipulate these.
Column K contains the total product volume produced. These will be constrained in different ways, as per your investigation (a), (b), and (c). It is =SUM(G3:J3) filled down.
Column L is the Lube Index for the product. As you noted, it is a linear blend - this is typically not true for blending problems. These values will be constrained in Solver. It is {=SUMPRODUCT(G3:J3,TRANSPOSE($B$2:$B$5))/$K3} filled down. Note that it is a Control-Shift-Enter (CSE) formula, required because of the TRANSPOSE.
Column M is the cost of the stock used to create the product. This is used in the Profit calculation. It is {=SUMPRODUCT(G3:J3,TRANSPOSE($C$2:$C$5))}, filled down. This is also a CSE formula.
Column N is the value of the product produced. This is used in the Profit calculation. It is =K3*C8 filled down.
Row 7 is the total stock volume used to generate all blends. These values will be constrained in Solver. It is =SUM(G3:G5), filled to the right.
The profit calculation is =SUM(N3:N5)-SUM(M3:M5).
Below is a snap of the Solver dialog box ...
It does the following ...
The objective is to maximize profit.
It will do this by manipulating the amount of stock that goes into each blend.
The first four constraints ($G$7 through $J$7) ensure the amount of stock available is not violated.
The next three constraints ($K$3 through $K$5) are for case (a) - make no more than product than there is demand.
The last three constraints ($L$3 through $L$5) make sure the lube index meets the minimum specification.
Not shown - I selected options for GRG Nonlinear and selected "Use Multistart" and deselected "Require Bounds on Variables".
Below is the result for case (a) ...
For case (b), change the constraints on Column K to be "=" instead of "<=". Below is the result ...
For case (c), change the constraints on Column K to be ">=". Below is the result ...
I think I came up with a solution, but I'm unsure if this is correct.
| Decision Variables | | | | | | | | | | | | | | | | |
|--------------------|---------|--------|--------|--------|-------------|--------|--------|--------|--------|--------|--------|--------|---|--------------------------------|----|------|
| | C1R | C1M | C1S | C2R | C2M | C2S | C3R | C3M | C3S | C4R | C4M | C4S | | | | |
| Inputs | 1000 | 0 | 0 | 800 | 0 | 300 | 0 | 1200 | 0 | 200 | 300 | 600 | | | | |
| | | | | | | | | | | | | | | | | |
| Objective Function | | | | | | | | | | | | | | Total Profit (Selling - Cost) | | |
| Cost | 7,10 € | 7,10 € | 7,10 € | 8,50 € | 8,50 € | 8,50 € | 7,70 € | 7,70 € | 7,70 € | 9,00 € | 9,00 € | 9,00 € | | 3.910,00 € | | |
| | | | | | | | | | | | | | | | | |
| Constraints | | | | | | | | | | | | | | LHS | | RHS |
| Regular | -5 | | | 15 | | | 5 | | | 30 | | | | 13000 | >= | 0 |
| Multi | | -15 | | | 5 | | | -5 | | | 20 | | | 0 | >= | 0 |
| Supreme | | | -30 | | | -10 | | | -20 | | | 5 | | 0 | >= | 0 |
| C1 Supply | 1 | 1 | 1 | | | | | | | | | | | 1000 | <= | 1000 |
| C2 Supply | | | | 1 | 1 | 1 | | | | | | | | 1100 | <= | 1100 |
| C3 Supply | | | | | | | 1 | 1 | 1 | | | | | 1200 | <= | 1200 |
| C4 Supply | | | | | | | | | | 1 | 1 | 1 | | 1100 | <= | 1100 |
| Regular Demand | 1 | | | 1 | | | 1 | | | 1 | | | | 2000 | >= | 2000 |
| Multi Demand | | 1 | | | 1 | | | 1 | | | 1 | | | 1500 | >= | 1500 |
| Supreme Demand | | | 1 | | | 1 | | | 1 | | | 1 | | 900 | >= | 750 |
| | | | | | | | | | | | | | | | | |
| | | | | | | | | | | | | | | | | |
| Selling | | | | | | | | | | | | | | | | |
| Regular | 8,50 € | x | 2000 | = | 17.000,00 € | | | | | | | | | | | |
| Multi | 9,00 € | x | 1500 | = | 13.500,00 € | | | | | | | | | | | |
| Supreme | 10,00 € | x | 900 | = | 9.000,00 € | | | | | | | | | | | |
| | | | | | 39.500,00 € | | | | | | | | | | | |
I have a file that has data stored in it the following way (weekly data example)
+----------+----------+----------+----------+----------+----------+
| | WK1 | WK2 | WK3 | WK4 | WK5 |
+----------+----------+----------+----------+----------+----------+
| DT Begin | 29.12.14 | 05.01.15 | 12.01.15 | 19.01.15 | 26.01.15 |
| DT End | 04.01.15 | 11.01.15 | 18.01.15 | 25.01.15 | 01.02.15 |
| XData | 50 | 10 | 10 | 10 | 50 |
+----------+----------+----------+----------+----------+----------+
My problem ist to aggregate the XData on a monthly basis. For that I want to break the data down for days and then calculate the average.
Edit: I changed the table as it was not clear what I meant. This averages to ((50*4)+(10*21)+(5*50))/31 = 22.90
+------------+-------+
| Date | Value |
+------------+-------+
| 01.01.2015 | 50 |
| 02.01.2015 | 50 |
| 03.01.2015 | 50 |
| 04.01.2015 | 50 |
| 05.01.2015 | 10 |
| 06.01.2015 | 10 |
| 07.01.2015 | 10 |
| 08.01.2015 | 10 |
| 09.01.2015 | 10 |
| 10.01.2015 | 10 |
| 11.01.2015 | 10 |
| 12.01.2015 | 10 |
| 13.01.2015 | 10 |
| 14.01.2015 | 10 |
| 15.01.2015 | 10 |
| 16.01.2015 | 10 |
| 17.01.2015 | 10 |
| 18.01.2015 | 10 |
| 19.01.2015 | 10 |
| 20.01.2015 | 10 |
| 21.01.2015 | 10 |
| 22.01.2015 | 10 |
| 23.01.2015 | 10 |
| 24.01.2015 | 10 |
| 25.01.2015 | 10 |
| 26.01.2015 | 50 |
| 27.01.2015 | 50 |
| 28.01.2015 | 50 |
| 29.01.2015 | 50 |
| 30.01.2015 | 50 |
| 31.01.2015 | 50 |
+------------+-------+
| Average | 22.90 |
+------------+-------+
After having done this calculation I want to summarize the data as follows for the entire year:
+-------+-------+-------+------+------+
| | Jan | Feb | Mar | ... |
+-------+-------+-------+------+------+
| XData | 22.90 | 22.00 | 23.1 | ... |
+-------+-------+-------+------+------+
Being a newbie in Excel VBA, I have extreme trouble doing this.
I know how to get to the value of a cell (Range.Value) but not how to find data in a particular week (as WK1 is there for 2014 as well) Range.Find with a date other than the one in the cell itself does not seem to work.
Whar I am asking for is a way to approach this problem. My particular difficulties are to:
Find the data in the worksheet
split the week values into day values (see table above)
Copy the data or hold it in some sort of data structure
calculate the average (this should be ease then)
fill in the data on a monthly basis
As you can see, I have trouble even getting started - any hints would be greatly appreciated. Maybe I'm thinking of this entirely too complicated? Thank you!