diff --git a/Greedy_iter/readme.md b/Greedy_iter/readme.md
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+  **Iterative greedy routine for the setcover problem**
diff --git a/Greedy_iter/solver.py b/Greedy_iter/solver.py
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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+# The MIT License (MIT)
+#
+# Copyright (c) 2014 Carleton Coffrin
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+# 
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+# 
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+
+
+from collections import namedtuple
+from heapq import heappush, heappop
+from random import shuffle, uniform
+from copy import deepcopy
+
+Set = namedtuple("Set", ['index', 'cost', 'items'])
+
+def solve_it(input_data):
+    # Modify this code to run your optimization algorithm
+
+    # parse the input
+    lines = input_data.split('\n')
+
+    parts = lines[0].split()
+    item_count = int(parts[0])
+    set_count = int(parts[1])
+    
+    sets = []
+    for i in range(1, set_count+1):
+        parts = lines[i].split()
+        sets.append(Set(i-1, float(parts[0]), map(int, parts[1:])))
+        
+    best_solution = [0]*set_count
+    sets_list = [i for i in range(set_count)]
+    best_obj = 1000000000.0
+    
+    for niter in range(25):
+        coverted = set()
+        solution = [0]*set_count
+        shuffle(sets_list)
+        while True:
+            h = []
+            for i in sets_list:
+                s = sets[i]
+                if solution[s.index] == 0:
+                    its = []
+                    for it in s.items:
+                        if it not in coverted:
+                            its.append(it)
+                    if len(its) > 0:
+                        heappush(h, (s.cost * uniform(0.85, 1.15) / len(its), s.index))
+            
+            if len(h) < 1:
+                print('error')
+                break
+            t = heappop(h)
+            #~ print(t)
+            solution[t[1]] = 1
+            coverted |= set(sets[t[1]].items)
+            if len(coverted) >= item_count:
+                break
+    
+        # calculate the cost of the solution
+        obj = sum([s.cost*solution[s.index] for s in sets])
+        if obj < best_obj:
+            best_obj = obj
+            best_solution = deepcopy(solution)
+
+    # prepare the solution in the specified output format
+    output_data = str(best_obj) + ' ' + str(0) + '\n'
+    output_data += ' '.join(map(str, best_solution))
+    
+
+    return output_data
+
+
+if __name__ == '__main__':
+    files_location = ['sc_157_0', 'sc_330_0', 'sc_1000_11', 'sc_5000_1', 'sc_10000_5', 'sc_10000_2']
+    i_file = 6
+    with open('./data/' + files_location[i_file - 1], 'r') as input_data_file:
+        input_data = input_data_file.read()
+    print(solve_it(input_data))
+
+#~ import sys
+
+#~ if __name__ == '__main__':
+    #~ import sys
+    #~ if len(sys.argv) > 1:
+        #~ file_location = sys.argv[1].strip()
+        #~ with open(file_location, 'r') as input_data_file:
+            #~ input_data = input_data_file.read()
+        #~ print(solve_it(input_data))
+    #~ else:
+        #~ print('This test requires an input file.  Please select one from the data directory. (i.e. python solver.py ./data/sc_6_1)')
+