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A single place for all revealed formulas.


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Wizzard Hicks
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Currently if you browse through these forums you can find a variety of formulas posted by Scott. Not only can it be very tedious to track all of these formulas down, sometimes the formulas change, but obviously the formulas in the post do not. This is could be off-putting for new players.

In order to help keep a level the playing field, could we get all revealed information in one place, and have it possibly kept updated when things change?
Walter Yorkshire
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FORMULAS

Factories
¤ Unit cost = 0.5 + 0.5 * (1 + Production_Quantity * Item_Base_Value^0.5 / 10000)^-0.25

Stores
¤ Product Demand (cents) = K * Total_Building_size * (1 + 0.02 * Q_avg) * POWER( MAX(1, 3*Product_Base_Value - Product_Avg_Price/10), 0.2);

R&D
¤ Research_Time = 500 * (Research_Level)^3 / (R&D_Size)



Excellent idea, I don't know how many times I have searched through dozens of topics because "I know that formula is around here somewhere!"

I will be editing this post as formulas are added so they will all appear near the top.
Bill Gates
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Formula's I'd like to see here:
The "Economies of Scale bonus" formula, i.e. the one which lowers the resources cost for producing in mass. e.g. if I produce 1 petroleum, It costs me 25 water and 25 electric. If I go to 10, that drops to just 247 for each, and further drops to only around 2200 if I go to 100.

A simple formula for the expansion effectiveness.

Maybe the formula which would explain store effectiveness when upgraded.

The formula used when expanding R&D, so that we know how far we have to expand a building to get X seconds, or whatever percentage of time off of production.

Definitely needed is the new tax, worker wage, etc. formulas, if I actually knew why and how I was having to pay for these, I could effectively reduce them.

Maybe a formula to explain where the exports get their prices from.
Mister Death
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I don't know what you mean by "store effectiveness", but the amount of product you sell is directly proportional to the size of your store. Double the size, you'll double your quantities.

The formula for R&D time, in seconds, is:

500 * (level)^3 / (size)

for level >= 2.
Tony Wooster
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From "Math of supermarkets v2.0", Mar 26:

TL;DR version of below:

num_sold = [max(0.3, (1+0.02*(quality-avg_quality))/price]^2 * ((0.3*avg_price+2*base_price)*category_mult)^2 * store_sqft * per_item_constant * (3/(1+2*pct_demand_met))^2

What this means is that as your quality shifts N units away from the average quality, your price must change by N*0.02*avg_price to match the same sales rate. In other words,

same_rate_price(quality, avg_quality, avg_price) = avg_price*(1+0.02*(quality-avg_quality))

"Below"

List of variables:
$price - Your product's listing price (in cents)
$quality - Your product's quality
$store_size - Your store size
$price_avg - World average price for this product (in cents)
$quality_avg - World average quality for this product
$price_base - This product's Wholesale Value as listed in the Pedia pages (in cents)
$selltime - A custom variable I can adjust to balance sales between very small and very large products, as of now it is at $price_base ^ 0.65 / 20, can also be changed manually for each product.
$category_price_multiplier - A category variable I can use to affect all products in a category (world events)

$n_sold - Number sold per tick. Partially sold units (< 1) will be carried over to the next tick(s).

Currently used equation:
$n_sold = $price_eq * $store_prod_eq
$price_eq = ( max(0.3, (1 + 0.02 * ($quality - $quality_avg)) ) / $price )^2
$store_prod_eq = ( (0.3 * $price_avg + 2 * $price_base) * $category_price_multiplier )^2 * $store_size / $selltime;

Next week's planned addition:
$n_sold = $price_eq * $store_prod_eq * demand_eq
$demand_eq = (3/(1 + 2*$demand_met))^2

demand_met is a decimal number calculated by supply/demand.
Demand Met % as shown in Pedia is equal to demand_met * 100%

From "Wages, maintenance and production math":

Concerning economies of scale:

unit cost = 0.5 + 0.5 * (1 + Production_Quantity * Item_Base_Value^0.5 / 10000)^-0.25;

Unit cost is a fraction between 0.5 to 1.0.
Base value is the Pedia value in cents.
Scott (Admin)
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Product Demand
Product Demand (cents) = K * Total_Building_size * (1 + 0.02 * Q_avg) * POWER( MAX(1, 3*Product_Base_Value - Product_Avg_Price/10), 0.2);

K = 150.
Nwabudike Morgan
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The cost of outsourcing research is a multiple of the cost of the research at that level. Where P is the proportion of research completed in the interval [0, 1):

Outsourcing Multiplier
M(P) = 21 - 40P + 20P^2

This means that research at 0% costs 21 times what you paid to start the research, and the outsourcing cost approaches the original research cost as progress approaches 100%. The best "bang for your buck" occurs at about 77.6% research completed, where the outsourcing cost is just twice the base research cost. That said, you only pay about 2.3x as much per second of research time saved if you just outsource immediately, and you save 4x as much time doing so.



The base research cost formula is exponential. Let C indicate the "Base Cost" of research from the eos-pedia, and let Q indicate the current quality level of research that has been completed.

Research Cost
For Q > 0: R(C,Q) = C * 1.2^Q
R(C,0) = 10*C
Nwabudike Morgan
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Advertising Effect
A(Power) = Power^0.25 (%)

You gain 100 Advertising Power per dollar spent on advertising, regardless of the size of your store. So, for example, if you spend $10,000 on a new store, you'll have 1M advertising power, which confers a 31.6% store sales bonus.

Advertising Decay
Advertising Power converges to 100/3 * store_size ^ 2 with a time constant of 1000/3 ticks (about half a week, since there are 96 ticks per day). About 1/e (~36.8%) of the difference between your current advertising power and the asymptote will remain after one time constant (3.47 days). About 1.8% of the difference between your current advertising power and the asymptote will remain after two weeks.
John Towler
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Factories
¤ Unit cost = 0.5 + 0.5 * (1 + Production_Quantity * Item_Base_Value^0.5 / 10000)^-0.25

This formula seems wrong. Empirically, I've tested my apples, and am coming up with the following values for each production quantity:

$ Elec Water %$ %Elect $Water Formula
1 0.14 0.1 3
100 13.88 10 298 99.14% 100.00% 99.33% 99.95%
1000 131.24 94 2813 93.74% 94.00% 93.77% 99.54%
10000 1115.30 797 23900 79.66% 79.70% 79.67% 96.18%
100000 9405.48 6719 201547 67.18% 67.19% 67.18% 83.88%



Edit: This table sucks. TL;DR: This is a much more accurate formula for economies of scale bonuses for production:

¤ Unit cost = 0.5 + 0.5 * (1 + Production_Quantity * Item_Base_Value^0.5 / CONSTANT)^-0.25

Where CONSTANT is roughly 525 right now.
Walter Yorkshire
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Did you do the unit cost in cents? I made that mistake at first when I imputed it into my spreadsheet. Otherwise the constant might be a variable which Scott controls and fine tunes.
John Towler
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Here's the formula I use for apples, that seems to be considerably more accurate:

Factor = = 0.5 + 0.5 * (1 + Production_Quantity * .14^0.5 / 525)^-0.25
Nwabudike Morgan
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am i right to say the bigger the store size, the faster your advertising will drop?

Incorrect! Actually, a larger store generates more advertising naturally, to the tune of 1/10 * store_size^2 per tick. As a result, a larger store's advertising converges to a larger asymptotic value. If the advertising power in two differently-sized stores is the same and both stores have more advertising than their steady-state values, then the larger store's advertising power will decay more slowly. This is because exponential decay is proportional to the difference between the current value and the asymptote. The store size changes that asymptote, but nothing else about advertising depends on store size.
Shan Van
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Product Demand
Product Demand (cents) = K * Total_Building_size * (1 + 0.02 * Q_avg) * POWER( MAX(1, 3*Product_Base_Value - Product_Avg_Price/10), 0.2);


What is "K" in this? I assume "Q" is quality..?
Scott (Admin)
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K is a constant, I believe it's at 150.
Tom Denton
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Not to mention the innumerable clicks required to keep two stores fully stocked....
My understanding (not sure if this has changed) is that your building maintenance fees are proportional to the square of the size of each building. So you end up with lower maintenance costs with two smaller buildings, but personally I'd much rather save on the time of keeping them both stocked and take the hit at the scale you're working at.
Nwabudike Morgan
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Building maintenance is linear with respect to the size of the building, I think 2% of the total cost. Salaries are taken as the 1.2 power (slightly superlinear, but much less than square), but with a smaller scalar factor.

Unless they've changed:

Maintenance = 2% of building cost
Salaries = $1 * size^1.2
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