feat(reproduction): add experiment4, altering elsewhere to allow inpu…

…t of upperBounds

reproduction/python_scripts/Experiment3.py

@@ -15,6 +15,7 @@
 file = '10-prescreened.txt'
 runs = 1
 objectiveTypes = [False, True, False]
+upperBounds = [60, 60, 60, 60]
 
 # Path to save results
 experimentFolder = '../python_outputs/experiment3'
@@ -51,7 +52,8 @@
      'population': scenario['population'],
      'generations': scenario['generations'],
      'objectiveTypes': objectiveTypes,
-     'solutionpath': scenario['solutionpath']}
+     'solutionpath': scenario['solutionpath'],
+     'upperBounds': upperBounds}
     for scenario in scenarios
 ]
 

reproduction/python_scripts/Experiment4.py

@@ -0,0 +1,70 @@
+# Experiment 4 (Figure 9)
+# Tri-objective model with 1, 2 or 3 greeters/line managers
+
+# Run time: TODO add runtime
+# (Intel Core i9-13900K with 81GB RAM running Pop!_OS 22.04 Linux)
+
+from os import listdir
+from os.path import isfile, join
+import datetime
+from multiprocessing import Pool
+from main import wrapper
+
+# Set to default
+mypath = r'../inputs'
+file = '10-prescreened.txt'
+runs = 1
+objectiveTypes = [False, True, False]
+population = 50
+generations = 25
+
+# Path to save results
+experimentFolder = '../python_outputs/experiment4'
+
+# Scenarios to run for this experiment
+scenarios = [
+    {
+        'upperBounds': [1, 60, 60, 60],
+        'solutionpath': join(experimentFolder, '1_line_manager')
+    },
+    {
+        'upperBounds': [2, 60, 60, 60],
+        'solutionpath': join(experimentFolder, '2_line_managers')
+    },
+    {
+        'upperBounds': [3, 60, 60, 60],
+        'solutionpath': join(experimentFolder, '3_line_managers')
+    }
+]
+
+# Start timer
+startTime = datetime.datetime.now()
+
+# Create parameter list for each experiment
+params = [
+    {'mypath': mypath,
+     'experimentFolder': experimentFolder,
+     'file': file,
+     'runs': runs,
+     'population': population,
+     'generations': generations,
+     'objectiveTypes': objectiveTypes,
+     'solutionpath': scenario['solutionpath'],
+     'upperBounds': scenario['upperBounds']}
+    for scenario in scenarios
+]
+
+# Create a process pool that uses all CPUs
+pool = Pool()
+try:
+    # Map the run_scenario function to the experiment files
+    results = pool.map(wrapper, params)
+finally:
+    # Close the pool and wait for the worker processes to finish
+    pool.close()
+    pool.join()
+
+# End timer and save time for that result
+endTime = datetime.datetime.now()
+with open(join(experimentFolder, "time.txt"), "w") as text_file:
+    text_file.write("{0}".format(endTime - startTime))

reproduction/python_scripts/ExperimentRunner.py

@@ -20,14 +20,15 @@
 
 class ExperimentRunner:
 
-    def __init__(self, seeds, parameterReader, objectiveTypes):
+    def __init__(self, seeds, parameterReader, objectiveTypes, upperBounds):
         self.archiver = inspyred.ec.archivers.best_archiver
         self.seeds = seeds
         self.prng = random.Random()
         self.prng.seed(seeds[0])
         self.parameterReader = parameterReader
         # Defines whether it is a bi-objective or tri-objective model
         self.objectiveTypes = objectiveTypes
+        self.upperBounds = upperBounds
 
     def run(self, runs, population, generations):
         solutions = []#store several solutions
@@ -36,7 +37,8 @@ def run(self, runs, population, generations):
         problem = StaffAllocationProblem.StaffAllocationProblem(
             seeds=self.seeds,
             parameterReader=self.parameterReader,
-            objectiveTypes=self.objectiveTypes)
+            objectiveTypes=self.objectiveTypes,
+            upperBounds=self.upperBounds)
 
         for i in xrange(1, runs + 1):
             print "Experiment Runner", i

reproduction/python_scripts/StaffAllocationProblem.py

@@ -23,7 +23,8 @@ def set_results_analyzer(self, resultsAnalyzer):
     def get_results_analyzer(self):
         return self.resultsAnalyzer
 class StaffAllocationProblem():
-    def __init__(self, seeds, parameterReader, objectiveTypes):
+    def __init__(self, seeds, parameterReader, objectiveTypes, upperBounds):
+
         # Defines whether it is a bi-objective or tri-objective model
         # E.g. objective types [False, True, False]
         #minimize Waiting time, minimize Resources, maximize throughput  
@@ -43,7 +44,7 @@ def __init__(self, seeds, parameterReader, objectiveTypes):
         #self.upperBounds = [8, 8, 25, 8] 
         #self.upperBounds = [1, 60, 60, 5]
         self.lowerBounds = [1, 1, 1, 1]
-        self.upperBounds = [60, 60, 60, 60]
+        self.upperBounds = upperBounds
 
         #self.bounder = inspyred.ec.Bounder(1, 4)
         self.bounder = inspyred.ec.Bounder(self.lowerBounds, self.upperBounds)

reproduction/python_scripts/main.py

@@ -10,7 +10,7 @@
 
 
 def run_scenario(mypath, experimentFolder, file, runs, population,
-                 generations, objectiveTypes, solutionpath=None):
+                 generations, objectiveTypes, upperBounds, solutionpath=None):
     '''
     Run algorithm using the pre-screened percentage from the provided file.
 
@@ -30,6 +30,9 @@ def run_scenario(mypath, experimentFolder, file, runs, population,
         Number of generations
     objectiveTypes : list
         List of booleans which define whether maximise/minimise 2/3 objectives
+    upperBounds : list of int
+        Maximum numbers of each staff type allowed - [greeter/line
+        manager, screener, dispenser, medic]
     solutionpath : string
         Optional, path to save solution to
     '''
@@ -41,7 +44,8 @@ def run_scenario(mypath, experimentFolder, file, runs, population,
                                                            file))
     experimentRunner = ExperimentRunner.ExperimentRunner(seeds,
                                                          parameterReader,
-                                                         objectiveTypes)
+                                                         objectiveTypes,
+                                                         upperBounds)
     experimentRunner.run(runs=runs,
                          population=population,
                          generations=generations)
@@ -75,7 +79,8 @@ def wrapper(d):
 
 
 def run_experiment(mypath, experimentFolder, experimentFiles, runs, population,
-                   generations, objectiveTypes, solutionpath=None):
+                   generations, objectiveTypes, solutionpath=None,
+                   upperBounds=[60, 60, 60, 60]):
     '''
     Run set of scenarios using parallel processing, and record time elapsed
 
@@ -100,6 +105,9 @@ def run_experiment(mypath, experimentFolder, experimentFiles, runs, population,
         List of booleans which define whether maximise/minimise 2/3 objectives
     solutionpath : string
         Optional, path to save solution to
+    upperBounds : list of int
+        Optional, maximum numbers of each staff type allowed - [greeter/line
+        manager, screener, dispenser, medic]
     '''
     # Start timer
     startTime = datetime.datetime.now()
@@ -113,7 +121,8 @@ def run_experiment(mypath, experimentFolder, experimentFiles, runs, population,
          'population': population,
          'generations': generations,
          'objectiveTypes': objectiveTypes,
-         'solutionpath': solutionpath}
+         'solutionpath': solutionpath,
+         'upperBounds': upperBounds}
         for file in experimentFiles
     ]