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PySCIPOpt: examples/finished/diet.py Source File

Go to the documentation of this file. 4 Copyright (c) by Joao Pedro PEDROSO and Mikio KUBO, 2012 7 from

pyscipopt

import

Model, quicksum, multidict

10 def diet

(F, N, a, b, c, d):

11 """diet -- model for the modern diet problem 15 - a[i]: minimum intake of nutrient i 16 - b[i]: maximum intake of nutrient i 17 - c[j]: cost of food j 18 - d[j][i]: amount of nutrient i in food j 19 Returns a model, ready to be solved. 22

model = Model(

"modern diet"

)

27

x[j] = model.addVar(vtype=

"I"

, name=

"x(%s)"

% j)

28

y[j] = model.addVar(vtype=

"B"

, name=

"y(%s)"

% j)

30

z[i] = model.addVar(lb=a[i], ub=b[i], name=

"z(%s)"

% j)

31

v = model.addVar(vtype=

"C"

, name=

"v"

)

35

model.addCons(

quicksum

(d[j][i] * x[j]

for

in

F) == z[i], name=

"Nutr(%s)"

% i)

37

model.addCons(

quicksum

(c[j] * x[j]

for

in

F) == v, name=

"Cost"

)

40

model.addCons(y[j] <= x[j], name=

"Eat(%s)"

% j)

43

model.setObjective(

quicksum

(y[j]

for

in

F),

"maximize"

)

44

model.data = x, y, z, v

50 """make_inst: prepare data for the diet model""" 52 "QPounder"

: [1.84, {

"Cal"

: 510,

"Carbo"

: 34,

"Protein"

: 28,

53 "VitA"

: 15,

"VitC"

: 6,

"Calc"

: 30,

"Iron"

: 20}],

54 "McLean"

: [2.19, {

"Cal"

: 370,

"Carbo"

: 35,

"Protein"

: 24,

"VitA"

: 15,

55 "VitC"

: 10,

"Calc"

: 20,

"Iron"

: 20}],

56 "Big Mac"

: [1.84, {

"Cal"

: 500,

"Carbo"

: 42,

"Protein"

: 25,

57 "VitA"

: 6,

"VitC"

: 2,

"Calc"

: 25,

"Iron"

: 20}],

58 "FFilet"

: [1.44, {

"Cal"

: 370,

"Carbo"

: 38,

"Protein"

: 14,

59 "VitA"

: 2,

"VitC"

: 0,

"Calc"

: 15,

"Iron"

: 10}],

60 "Chicken"

: [2.29, {

"Cal"

: 400,

"Carbo"

: 42,

"Protein"

: 31,

61 "VitA"

: 8,

"VitC"

: 15,

"Calc"

: 15,

"Iron"

: 8}],

62 "Fries"

: [.77, {

"Cal"

: 220,

"Carbo"

: 26,

"Protein"

: 3,

63 "VitA"

: 0,

"VitC"

: 15,

"Calc"

: 0,

"Iron"

: 2}],

64 "McMuffin"

: [1.29, {

"Cal"

: 345,

"Carbo"

: 27,

"Protein"

: 15,

65 "VitA"

: 4,

"VitC"

: 0,

"Calc"

: 20,

"Iron"

: 15}],

66 "1% LFMilk"

: [.60, {

"Cal"

: 110,

"Carbo"

: 12,

"Protein"

: 9,

67 "VitA"

: 10,

"VitC"

: 4,

"Calc"

: 30,

"Iron"

: 0}],

68 "OrgJuice"

: [.72, {

"Cal"

: 80,

"Carbo"

: 20,

"Protein"

: 1,

69 "VitA"

: 2,

"VitC"

: 120,

"Calc"

: 2,

"Iron"

: 2}],

73 "Cal"

: [2000,

None

75 "Protein"

: [55,

None

76 "VitA"

: [100,

None

77 "VitC"

: [100,

None

78 "Calc"

: [100,

None

79 "Iron"

: [100,

None

82 return

F, N, a, b, c, d

85 if

__name__ ==

"__main__"

89 for

"Cal"

]

in

[

None

, 3500, 3000, 2500]:

91

print(

"\nDiet for a maximum of {0} calories"

.format(b[

"Cal"

]

if

"Cal"

] !=

None else "unlimited"

))

92

model =

diet

(F, N, a, b, c, d)

96

print(

"Optimal value:"

, model.getObjVal())

97

x, y, z, v = model.data

99 if

model.getVal(x[j]) > 0:

100

print(

"{0:30s}: {1:3.1f} dishes --> {2:4.2f} added to objective"

.format(j, model.getVal(x[j]),

102

print(

"amount spent:"

, model.getObjVal())

104

print(

"amount of nutrients:"

)

106

print(

"{0:30s}: {1:4.2f}"

.format(i, model.getVal(z[i])))

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