add knapsack model

README.md

@@ -81,6 +81,7 @@ List of models under `models` directory is listed below. Most models have a GAMS
 | [InternationalMeanVar](models/InternationalMeanVar)           | [InternationalMeanVar](https://www.gams.com/latest/finlib_ml/libhtml/finlib_InternationalMeanVar.html)               | NLP           | Demo             |
 | [invmat](models/invmat)                                       |                                                                                                                      | LP            | Demo             |
 | [iobalance](models/iobalance)                                 | [iobalance](https://www.gams.com/latest/gamslib_ml/libhtml/gamslib_iobalance.html)                                   | LP, NLP, QCP  | Demo             |
+| [knapsack](models/knapsack)                                       |                                          | MIP           | Demo             |
 | [korcns](models/korcns)                                       | [korcns](https://www.gams.com/latest/gamslib_ml/libhtml/gamslib_korcns.html)                                         | CNS           | Demo             |
 | [linear](models/linear)                                       | [linear](https://www.gams.com/latest/gamslib_ml/libhtml/gamslib_linear.html)                                         | DNLP, LP, NLP | Demo             |
 | [lop](models/lop)                                             | [lop](https://www.gams.com/latest/gamslib_ml/libhtml/gamslib_lop.html)                                               | LP, MIP       | Demo             |

models/knapsack/f1_l-d_kp_10_269

@@ -0,0 +1,11 @@
+10 269
+55 95
+10 4
+47 60
+5 32
+4 23
+50 72
+8 80
+61 62
+85 65
+87 46

models/knapsack/knapsack.py

@@ -0,0 +1,82 @@
+import math
+import sys
+from pathlib import Path
+
+from gamspy import (
+    Container,
+    Equation,
+    Model,
+    Parameter,
+    Problem,
+    Sense,
+    Set,
+    Sum,
+    Variable,
+    VariableType,
+)
+
+# Declaration
+m = Container()
+i = Set(m, "i", description="items")
+p = Parameter(m, "p", description="profits", domain=i)
+w = Parameter(m, "p", description="weights", domain=i)
+c = Parameter(m, "c", description="capacity")
+x = Variable(m, "x", domain=i, description="chosen", type=VariableType.BINARY)
+
+cap_restr = Equation(m, name="capacity_restriction")
+cap_restr[...] = Sum(i, w[i] * x[i]) <= c
+
+utility = Sum(i, p[i] * x[i])
+
+knapsack = Model(
+    m,
+    name="knapsack",
+    equations=m.getEquations(),
+    problem=Problem.MIP,
+    sense=Sense.MAX,
+    objective=utility,
+)
+
+
+# Instance data
+def load_instance_from_file(filename):
+    def ints(elems):
+        return [int(elem) for elem in elems]
+
+    global items, capacity, profits, weights
+    items, capacity, profits, weights = [], [], [], []
+    num_items = None
+    with open(filename) as fp:
+        for line in fp.readlines():
+            if not line.strip():
+                continue
+            parts = line.split()
+            assert len(parts) == 2
+            if not num_items:
+                num_items, capacity = ints(parts)
+                continue
+            profits.append(parts[0])
+            weights.append(parts[1])
+    assert num_items
+    items = [f"i{i + 1}" for i in range(num_items)]
+
+
+# Example instance taken from
+# http://artemisa.unicauca.edu.co/~johnyortega/instances_01_KP/
+# and also available at https://github.com/JordiHOFC/knapsackproblemboolean
+load_instance_from_file(
+    str(Path(__file__).parent.absolute()) + "/f1_l-d_kp_10_269"
+)
+i.setRecords(items)
+p.setRecords(zip(items, profits))
+w.setRecords(zip(items, weights))
+c.setRecords(capacity)
+
+# Run solve and display results
+knapsack.solve(output=sys.stdout)
+print(f"Objective function value = {knapsack.objective_value}")
+assert math.isclose(knapsack.objective_value, 269.0, rel_tol=0.001)
+levels = list(x.records["level"])
+print(
+    f'Chosen items = {", ".join([j for ix, j in enumerate(items) if levels[ix] == 1.0])}'
+)