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-rw-r--r--glpk-5.0/examples/csv/distances.csv7
-rw-r--r--glpk-5.0/examples/csv/markets.csv4
-rw-r--r--glpk-5.0/examples/csv/parameters.csv2
-rw-r--r--glpk-5.0/examples/csv/plants.csv3
-rw-r--r--glpk-5.0/examples/csv/transp_csv.mod70
5 files changed, 86 insertions, 0 deletions
diff --git a/glpk-5.0/examples/csv/distances.csv b/glpk-5.0/examples/csv/distances.csv
new file mode 100644
index 0000000..8c7b419
--- /dev/null
+++ b/glpk-5.0/examples/csv/distances.csv
@@ -0,0 +1,7 @@
+plant,market,distance
+"Seattle","New York",2.5
+"Seattle","Chicago",1.7
+"Seattle","Topeka",1.8
+"San Diego","New York",2.5
+"San Diego","Chicago",1.8
+"San Diego","Topeka",1.4
diff --git a/glpk-5.0/examples/csv/markets.csv b/glpk-5.0/examples/csv/markets.csv
new file mode 100644
index 0000000..d04dec8
--- /dev/null
+++ b/glpk-5.0/examples/csv/markets.csv
@@ -0,0 +1,4 @@
+market,demand
+"New York",325.
+"Chicago",300.
+"Topeka",275.
diff --git a/glpk-5.0/examples/csv/parameters.csv b/glpk-5.0/examples/csv/parameters.csv
new file mode 100644
index 0000000..c7c37e9
--- /dev/null
+++ b/glpk-5.0/examples/csv/parameters.csv
@@ -0,0 +1,2 @@
+parameter,value
+"transport cost",90.
diff --git a/glpk-5.0/examples/csv/plants.csv b/glpk-5.0/examples/csv/plants.csv
new file mode 100644
index 0000000..292f45f
--- /dev/null
+++ b/glpk-5.0/examples/csv/plants.csv
@@ -0,0 +1,3 @@
+plant,capacity
+"Seattle",350.
+"San Diego",600.
diff --git a/glpk-5.0/examples/csv/transp_csv.mod b/glpk-5.0/examples/csv/transp_csv.mod
new file mode 100644
index 0000000..d970bf6
--- /dev/null
+++ b/glpk-5.0/examples/csv/transp_csv.mod
@@ -0,0 +1,70 @@
+# A TRANSPORTATION PROBLEM
+#
+# This problem finds a least cost shipping schedule that meets
+# requirements at markets and supplies at factories.
+#
+# References:
+# Dantzig G B, "Linear Programming and Extensions."
+# Princeton University Press, Princeton, New Jersey, 1963,
+# Chapter 3-3.
+
+set I;
+/* canning plants */
+
+set J;
+/* markets */
+
+set K dimen 2;
+/* transportation lane */
+
+set L;
+/* parameters */
+
+param a{i in I};
+/* capacity of plant i in cases */
+
+param b{j in J};
+/* demand at market j in cases */
+
+param d{i in I, j in J};
+/* distance in thousands of miles */
+
+param e{l in L};
+/* parameters */
+
+param f;
+/* freight in dollars per case per thousand miles */
+
+table tab_plant IN "CSV" "plants.csv" :
+ I <- [plant], a ~ capacity;
+
+table tab_market IN "CSV" "markets.csv" :
+ J <- [market], b ~ demand;
+
+table tab_distance IN "CSV" "distances.csv" :
+ K <- [plant, market], d ~ distance;
+
+table tab_parameter IN "CSV" "parameters.csv" :
+ L <- [parameter], e ~ value ;
+
+param c{i in I, j in J} := e['transport cost'] * d[i,j] / 1000;
+/* transport cost in thousands of dollars per case */
+
+var x{(i,j) in K} >= 0;
+/* shipment quantities in cases */
+
+minimize cost: sum{(i,j) in K} c[i,j] * x[i,j];
+/* total transportation costs in thousands of dollars */
+
+s.t. supply{i in I}: sum{(i,j) in K} x[i,j] <= a[i];
+/* observe supply limit at plant i */
+
+s.t. demand{j in J}: sum{(i,j) in K} x[i,j] >= b[j];
+/* satisfy demand at market j */
+
+solve;
+
+table tab_result{(i,j) in K} OUT "CSV" "result.csv" :
+ i ~ plant, j ~ market, x[i,j] ~ shipment;
+
+end;