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90 changes: 45 additions & 45 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -59,25 +59,25 @@ Rulp is inspired by the ruby wrapper for the GLPK toolkit and the python LP libr

given[

X_i >= 0,
Y_i >= 0,
Z_i >= 0
X_lpi >= 0,
Y_lpi >= 0,
Z_lpi >= 0

]

result = Rulp::Max( 10 * X_i + 6 * Y_i + 4 * Z_i ) [
X_i + Y_i + Z_i <= 100,
10 * X_i + 4 * Y_i + 5 * Z_i <= 600,
2 * X_i + 2 * Y_i + 6 * Z_i <= 300
result = Rulp::Max( 10 * X_lpi + 6 * Y_lpi + 4 * Z_lpi ) [
X_lpi + Y_lpi + Z_lpi <= 100,
10 * X_lpi + 4 * Y_lpi + 5 * Z_lpi <= 600,
2 * X_lpi + 2 * Y_lpi + 6 * Z_lpi <= 300
].solve

##
# 'result' is the result of the objective function.
# You can retrieve the values of variables by using the 'value' method
# E.g
# X_i.value == 32
# Y_i.value == 67
# Z_i.value == 0
# X_lpi.value == 32
# Y_lpi.value == 67
# Z_lpi.value == 0
##
```

Expand Down Expand Up @@ -189,18 +189,18 @@ At this point, you should have GLPK installed. Verify it:
# need to initialize them.
# They follow a naming convention that defines their type.
# A variable is declared as a constant with one of three different suffixes.
# 'f' or '_f' indicates a general variable (No constraints)
# 'i' or '_i' indicates a integer variable
# 'b' or '_b' indicates a binary/boolean variable
# 'lpf' or '_lpf' indicates a general variable (No constraints)
# 'lpi' or '_lpi' indicates a integer variable
# 'lpb' or '_lpb' indicates a binary/boolean variable


An_Integer_i
An_Integer_lpi
=> #<IV:0x007ffc4b651b80 @name="An_Integer">

Generalf
Generallpf
=> #<LV:0x007ffc4b651b80 @name="General">

Bool_Val_b
Bool_Val_lpb
=> #<BV:0x007ffc4b67b6b0 @name="Bool_Val">

# In some cases it is implausible to generate a unique name for every possible variable
Expand All @@ -209,13 +209,13 @@ At this point, you should have GLPK installed. Verify it:
# accept index parameters to create large ranges of unique variables.
# Examples of how indexed variables can be declared are as follows:

Item_i(4,5)
Item_lpi(4,5)
#<IV:0x007ffc4b3ea518 @name="Item4_5">

Item_i("store_3", "table_2")
Item_lpi("store_3", "table_2")
#<IV:0x007ffc4b3a3cd0 @name="Itemstore_3_table_2">

[*0..10].map(&Unit_f)
[*0..10].map(&Unit_lpf)
=> [#<LV:0x007ffc4cc25768 @name="Unit0">,
#<LV:0x007ffc4cc24cf0 @name="Unit1">,
#<LV:0x007ffc4cc0fc88 @name="Unit2">,
Expand All @@ -237,16 +237,16 @@ Constraints on a variable can only use numeric literals and not other variables.
Inter-variable constraints should be expressed as problem constrants. (Explained below.)

```ruby
X_i < 5
X_i.bounds
X_lpi < 5
X_lpi.bounds
=> "X <= 5"

3 <= X_i < 15
3 <= X_lpi < 15
X_i.bounds
=> "3 <= X <= 15"

Y_f == 10
Y_f.bounds
Y_lpf == 10
Y_lpf.bounds
=> "y = 10"
```

Expand All @@ -255,14 +255,14 @@ Inter-variable constraints should be expressed as problem constrants. (Explained
Constraints are added to a problem using the :[] syntax.

```ruby
problem = Rulp::Max( 10 * X_i + 6 * Y_i + 4 * Z_i )
problem = Rulp::Max( 10 * X_lpi + 6 * Y_lpi + 4 * Z_lpi )

problem[
X_i + Y_i + Z_i <= 100
X_lpi + Y_lpi + Z_lpi <= 100
]

problem[
10 * X_i + 4 * Y_i + 5 * Z_i <= 600
10 * X_lpi + 4 * Y_lpi + 5 * Z_lpi <= 600
]
...
problem.solve
Expand All @@ -271,10 +271,10 @@ Constraints are added to a problem using the :[] syntax.
You can add multiple constraints at once by comma separating them as seen in the earlier examples:

```ruby
Rulp::Max( 10 * X_i + 6 * Y_i + 4 * Z_i ) [
X_i + Y_i + Z_i <= 100,
10 * X_i + 4 * Y_i + 5 * Z_i <= 600,
2 * X_i + 2 * Y_i + 6 * Z_i <= 300
Rulp::Max( 10 * X_lpi + 6 * Y_lpi + 4 * Z_lpi ) [
X_lpi + Y_lpi + Z_lpi <= 100,
10 * X_lpi + 4 * Y_lpi + 5 * Z_lpi <= 600,
2 * X_lpi + 2 * Y_lpi + 6 * Z_lpi <= 300
]
```

Expand All @@ -288,10 +288,10 @@ such that the command `which [exec_name]` returns a path. (I.e they must be on y
Given a problem there are multiple ways to initiate a solver.

```ruby
@problem = Rulp::Max( 10 * X_i + 6 * Y_i + 4 * Z_i ) [
X_i + Y_i + Z_i <= 100,
10 * X_i + 4 * Y_i + 5 * Z_i <= 600,
2 * X_i + 2 * Y_i + 6 * Z_i <= 300
@problem = Rulp::Max( 10 * X_lpi + 6 * Y_lpi + 4 * Z_lpi ) [
X_lpi + Y_lpi + Z_lpi <= 100,
10 * X_lpi + 4 * Y_lpi + 5 * Z_lpi <= 600,
2 * X_lpi + 2 * Y_lpi + 6 * Z_lpi <= 300
]
```

Expand Down Expand Up @@ -410,13 +410,13 @@ You can then play with and attempt LP and MIP problems straight from the command

```ruby

[1] pry(main)> 13 <= X_i <= 45 # Declare integer variable
[1] pry(main)> 13 <= X_lpi <= 45 # Declare integer variable
=> X(i)[undefined]

[2] pry(main)> -15 <= Y_f <= 15 # Declare float variable
[2] pry(main)> -15 <= Y_lpf <= 15 # Declare float variable
=> Y(f)[undefined]

[3] pry(main)> @problem = Rulp::Min(X_i - Y_f) # Create min problem
[3] pry(main)> @problem = Rulp::Min(X_lpi - Y_lpf) # Create min problem
[info] Creating minimization problem
=>
Minimize
Expand All @@ -430,7 +430,7 @@ You can then play with and attempt LP and MIP problems straight from the command
X
End

[4] @problem[ X_i - 2 * Y_f < 40] #Adding a problem constraint
[4] @problem[ X_lpi - 2 * Y_lpf < 40] #Adding a problem constraint
=>
Minimize
obj: X -Y
Expand All @@ -450,21 +450,21 @@ You can then play with and attempt LP and MIP problems straight from the command
[info] Parsing result
=> -2.0 #(Minimal result)

[6] pry(main)> Y_f # See value calculated for Y now that solver has run
[6] pry(main)> Y_lpf # See value calculated for Y now that solver has run
=> Y(f)[15.0]

[8] pry(main)> X_i
[8] pry(main)> X_lpi
=> X(i)[13.0]

# The result of the objective function (-2.0) was returned by the call to .solve
# Now the solver has run and calculated values for our variables we can also test the
# objective function (or any function) by calling evaluate on it.
# E.g

[9] (X_i - Y_f).evaluate
[9] (X_lpi - Y_lpf).evaluate
=> -2.0

[10] pry(main)> (2 * X_i + 15 * Y_f).evaluate
[10] pry(main)> (2 * X_lpi + 15 * Y_lpf).evaluate
=> 251.0
```

Expand All @@ -481,7 +481,7 @@ we don't. We can't partially purchase one.)
```ruby
# Generate the data randomly for this example.
costs, points = [*0..1000].map do |i|
[Purchase_b(i) * Random.rand(1.0..3.0), Purchase_b(i) * Random.rand(5.0..10.0)]
[Purchase_lpb(i) * Random.rand(1.0..3.0), Purchase_lpb(i) * Random.rand(5.0..10.0)]
end.transpose.map(&:sum) #We sum the array of points and array of costs to create a Rulp expression

# And this is where the magic happens!. We ask rulp to maximise the number of points given
Expand All @@ -493,7 +493,7 @@ Rulp::Max(points)[
=> 538.2125623353652 (# You will get a different value as data was generated randomly)

# Now how do we check which purchases were selected?
selected_purchases = [*0..1000].map(&Purchase_b).select(&:selected?)
selected_purchases = [*0..1000].map(&Purchase_lpb).select(&:selected?)

=> [Purchase27(b)[true],
Purchase86(b)[true],
Expand Down
6 changes: 3 additions & 3 deletions examples/boolean_example.rb
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Expand Up @@ -9,7 +9,7 @@
#
##

items = 50.times.map(&Shop_Item_b)
items = 50.times.map(&Shop_Item_lpb)
items_count = items.sum
items_costs = items.map{|item| item * Random.rand(1.0...5.0)}.sum

Expand All @@ -25,5 +25,5 @@
# 'cost' is the result of the objective function.
# You can retrieve allocations by querying the variables.
# E.g
# Shop_Item_b(4).value
##
# Shop_Item_lpb(4).value
##
22 changes: 11 additions & 11 deletions examples/simple_example.rb
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Expand Up @@ -18,16 +18,16 @@

given[

X_i >= 0,
Y_i >= 0,
Z_i >= 0
X_lpi >= 0,
Y_lpi >= 0,
Z_lpi >= 0

]

Rulp::Max( objective = 10 * X_i + 6 * Y_i + 4 * Z_i ) [
X_i + Y_i + Z_i <= 100,
10 * X_i + 4 * Y_i + 5 * Z_i <= 600,
2 * X_i + 2 * Y_i + 6 * Z_i <= 300
Rulp::Max( objective = 10 * X_lpi + 6 * Y_lpi + 4 * Z_lpi ) [
X_lpi + Y_lpi + Z_lpi <= 100,
10 * X_lpi + 4 * Y_lpi + 5 * Z_lpi <= 600,
2 * X_lpi + 2 * Y_lpi + 6 * Z_lpi <= 300
].cbc

result = objective.evaluate
Expand All @@ -36,7 +36,7 @@
# 'result' is the result of the objective function.
# You can retrieve the values of variables by using the 'value' method
# E.g
# X_i.value == 32
# Y_i.value == 67
# Z_i.value == 0
##
# X_lpi.value == 32
# Y_lpi.value == 67
# Z_lpi.value == 0
##
14 changes: 7 additions & 7 deletions examples/whiskas_model2.rb
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Expand Up @@ -5,7 +5,7 @@
#
require_relative "../lib/rulp"

ingredients = [Chicken_i, Beef_i, Mutton_i, Rice_i, Wheat_i, Gel_i]
ingredients = [Chicken_lpi, Beef_lpi, Mutton_lpi, Rice_lpi, Wheat_lpi, Gel_lpi]
costs = {Chicken: 0.013, Beef: 0.008, Mutton: 0.010, Rice: 0.002, Wheat: 0.005, Gel: 0.001}
protein_percent = {Chicken: 0.100, Beef: 0.200, Mutton: 0.150, Rice: 0.000, Wheat: 0.040, Gel: 0.000}
fat_percent = {Chicken: 0.080, Beef: 0.100, Mutton: 0.110, Rice: 0.010, Wheat: 0.010, Gel: 0.000}
Expand All @@ -26,9 +26,9 @@

puts "Total Cost Per Can: #{result}"
puts
puts "Chicken: #{Chicken_i.value}"
puts "Beef: #{Beef_i.value}"
puts "Mutton: #{Mutton_i.value}"
puts "Rice: #{Rice_i.value}"
puts "Wheat: #{Wheat_i.value}"
puts "Gel: #{Gel_i.value}"
puts "Chicken: #{Chicken_lpi.value}"
puts "Beef: #{Beef_lpi.value}"
puts "Mutton: #{Mutton_lpi.value}"
puts "Rice: #{Rice_lpi.value}"
puts "Wheat: #{Wheat_lpi.value}"
puts "Gel: #{Gel_lpi.value}"
20 changes: 10 additions & 10 deletions lib/extensions/kernel_extensions.rb
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Expand Up @@ -7,11 +7,11 @@
# This is similar to the syntax defined in the object extensions but allows for numbered
# suffixes to quickly generate ranges of similar variables.
#
# Where lp var type suffix is either _b for binary, _i for integer, or _f for float.
# Where lp var type suffix is either _lpb for binary, _lpi for integer, or _lpf for float.
# I.e
#
# Rating_i(5) is the equivalent of Rating_5 (type integer)
# Is_happy_b(2) is the equivalent of Is_happy_2 (type binary/boolean)
# Rating_lpi(5) is the equivalent of Rating_5 (type integer)
# Is_happy_lpb(2) is the equivalent of Is_happy_2 (type binary/boolean)
# ...
##
module Kernel
Expand All @@ -20,15 +20,15 @@ def method_missing(value, *args)
method_name = "#{value}" rescue ""
start = method_name[0]
if (start <= "Z" && start >= "A")
case method_name[-1]
when "b"
method_name = method_name[0..(method_name[-2] == "_" ? -3 : -2)]
case method_name[-3..-1]
when "lpb"
method_name = method_name[0..(method_name[-4] == "_" ? -5 : -4)]
return BV.definition(method_name, args)
when "i"
method_name = method_name[0..(method_name[-2] == "_" ? -3 : -2)]
when "lpi"
method_name = method_name[0..(method_name[-4] == "_" ? -5 : -4)]
return IV.definition(method_name, args)
when "f"
method_name = method_name[0..(method_name[-2] == "_" ? -3 : -2)]
when "lpf"
method_name = method_name[0..(method_name[-4] == "_" ? -5 : -4)]
return LV.definition(method_name, args)
end
end
Expand Down
20 changes: 10 additions & 10 deletions lib/extensions/object_extensions.rb
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Expand Up @@ -4,23 +4,23 @@
#
# [Capitalized_varname][lp var type suffix]
#
# Where lp var type suffix is either _b for binary, _i for integer, or _f for float.
# Where lp var type suffix is either _lpb for binary, _lpi for integer, or _lpf for float.
# I.e
#
# Rating_i is the equivalent of Rating (type integer)
# Is_happy_b is the equivalent of Is_happy (type binary/boolean)
# Rating_lpi is the equivalent of Rating (type integer)
# Is_happy_lpb is the equivalent of Is_happy (type binary/boolean)
##
class << Object
alias_method :old_const_missing, :const_missing
def const_missing(value)
method_name = "#{value}".split("::")[-1] rescue ""
if (("A".."Z").include?(method_name[0]))
if(method_name.end_with?("b"))
return BV.definition(method_name[0..(method_name[-2] == "_" ? -3 : -2)])
elsif(method_name.end_with?("i"))
return IV.definition(method_name[0..(method_name[-2] == "_" ? -3 : -2)])
elsif(method_name.end_with?("f"))
return LV.definition(method_name[0..(method_name[-2] == "_" ? -3 : -2)])
if ("A".."Z").include?(method_name[0])
if(method_name.end_with?("lpb"))
return BV.definition(method_name[0..(method_name[-4] == "_" ? -5 : -4)])
elsif(method_name.end_with?("lpi"))
return IV.definition(method_name[0..(method_name[-4] == "_" ? -5 : -4)])
elsif(method_name.end_with?("lpf"))
return LV.definition(method_name[0..(method_name[-4] == "_" ? -5 : -4)])
end
end
old_const_missing(value)
Expand Down
8 changes: 4 additions & 4 deletions lib/rulp/lv.rb
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Expand Up @@ -22,7 +22,7 @@ def meth
end

def suffix
"f"
"lpf"
end

def self.definition(name, *args)
Expand Down Expand Up @@ -75,11 +75,11 @@ def inspect

class BV < LV;
def suffix
"b"
"lpb"
end
end
class IV < LV;
def suffix
"i"
"lpi"
end
end
end
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