minor updates, added script for paper and configs

configs/easy.yaml

@@ -0,0 +1,72 @@
+####################
+# initial settings #
+####################
+t_0: '10:30'                    # initial clock time
+T: 2.0                          # [h]
+delta_t: 0.25                   # [h]
+c_init: 1.0                     # initial soc of nodes 
+p_init: 0.0                     # initial soc of producers
+vehicle_init: 0.1               # initial soc of vehicles 
+
+
+##################
+# Data locations #
+##################
+vehicle_dir: 'data/vehicles'
+depot_dir: 'data/depots'
+consumer_dir: 'data/paper/c_easy.csv'
+producer_dir: 'data/paper/p_all.csv'
+other_dir: 'data/others'
+
+
+#####################
+# Data restrictions #
+#####################
+v_max: 40
+c_max: 1
+p_max: 1
+o_max: 0
+d_max: 1
+lat: [49.00, 49.90]     # min and max vals
+lon: [7.50, 7.90]
+
+
+##################
+# Model settings #
+##################
+objective: 0
+constr_j: True          # (1j) valid inequality
+min_vehicles: True      # toggle obj and constraints connected to z
+limit_vehicles: True    # (1l) limit charging vehicles at locations
+visualize: False         # visualize solution
+constrain_vehicles: 12  # only allow leq this many vehicles being used 
+
+######################
+# Heuristic settings #
+######################
+h_init_time_limit: 120
+h_time_limit: 60
+h_init: quick           # [quick, greedy]
+
+
+###################
+# Gurobi settings #
+###################
+TimeLimit: 100000
+threads: 1
+# multiple threads for parallel work
+# can be restricted in order to save RAM
+method: -1
+# method used to solve root relaxation (only root!)
+# -1: default 1: dual-simplex 2: barrier 
+MIPFocus: 0
+# 0: default, balance between both
+# 1: focus on finding feasible solutions 
+# 2: more attention on proving optimality
+# 3: if best bound is barely moving 
+MIPGap: 0.0001    
+# default: 0.0001
+CutPasses: -1
+# default: -1
+write_lp: False
+LogToConsole: True

configs/extreme.yaml

@@ -0,0 +1,72 @@
+####################
+# initial settings #
+####################
+t_0: '10:30'                    # initial clock time
+T: 2.0                          # [h]
+delta_t: 0.25                   # [h]
+c_init: 1.0                     # initial soc of nodes 
+p_init: 0.0                     # initial soc of producers
+vehicle_init: 0.1               # initial soc of vehicles 
+
+
+##################
+# Data locations #
+##################
+vehicle_dir: 'data/vehicles'
+depot_dir: 'data/depots'
+consumer_dir: 'data/paper/c_extreme.csv'
+producer_dir: 'data/paper/p_all.csv'
+other_dir: 'data/others'
+
+
+#####################
+# Data restrictions #
+#####################
+v_max: 40
+c_max: 1
+p_max: 1
+o_max: 0
+d_max: 1
+lat: [49.00, 49.90]     # min and max vals
+lon: [7.50, 7.90]
+
+
+##################
+# Model settings #
+##################
+objective: 0
+constr_j: True          # (1j) valid inequality
+min_vehicles: True      # toggle obj and constraints connected to z
+limit_vehicles: True    # (1l) limit charging vehicles at locations
+visualize: False         # visualize solution
+constrain_vehicles: 12  # only allow leq this many vehicles being used 
+
+######################
+# Heuristic settings #
+######################
+h_init_time_limit: 120
+h_time_limit: 60
+h_init: quick           # [quick, greedy]
+
+
+###################
+# Gurobi settings #
+###################
+TimeLimit: 100000
+threads: 1
+# multiple threads for parallel work
+# can be restricted in order to save RAM
+method: -1
+# method used to solve root relaxation (only root!)
+# -1: default 1: dual-simplex 2: barrier 
+MIPFocus: 0
+# 0: default, balance between both
+# 1: focus on finding feasible solutions 
+# 2: more attention on proving optimality
+# 3: if best bound is barely moving 
+MIPGap: 0.0001    
+# default: 0.0001
+CutPasses: -1
+# default: -1
+write_lp: False
+LogToConsole: True

configs/moderate.yaml

@@ -0,0 +1,72 @@
+####################
+# initial settings #
+####################
+t_0: '10:30'                    # initial clock time
+T: 2.0                          # [h]
+delta_t: 0.25                   # [h]
+c_init: 1.0                     # initial soc of nodes 
+p_init: 0.0                     # initial soc of producers
+vehicle_init: 0.1               # initial soc of vehicles 
+
+
+##################
+# Data locations #
+##################
+vehicle_dir: 'data/vehicles'
+depot_dir: 'data/depots'
+consumer_dir: 'data/paper/c_moderate.csv'
+producer_dir: 'data/paper/p_all.csv'
+other_dir: 'data/others'
+
+
+#####################
+# Data restrictions #
+#####################
+v_max: 40
+c_max: 1
+p_max: 1
+o_max: 0
+d_max: 1
+lat: [49.00, 49.90]     # min and max vals
+lon: [7.50, 7.90]
+
+
+##################
+# Model settings #
+##################
+objective: 0
+constr_j: True          # (1j) valid inequality
+min_vehicles: True      # toggle obj and constraints connected to z
+limit_vehicles: True    # (1l) limit charging vehicles at locations
+visualize: False        # visualize solution
+constrain_vehicles: 12  # only allow leq this many vehicles being used 
+
+######################
+# Heuristic settings #
+######################
+h_init_time_limit: 120
+h_time_limit: 60
+h_init: quick           # [quick, greedy]
+
+
+###################
+# Gurobi settings #
+###################
+TimeLimit: 100000
+threads: 1
+# multiple threads for parallel work
+# can be restricted in order to save RAM
+method: -1
+# method used to solve root relaxation (only root!)
+# -1: default 1: dual-simplex 2: barrier 
+MIPFocus: 0
+# 0: default, balance between both
+# 1: focus on finding feasible solutions 
+# 2: more attention on proving optimality
+# 3: if best bound is barely moving 
+MIPGap: 0.0001    
+# default: 0.0001
+CutPasses: -1
+# default: -1
+write_lp: False
+LogToConsole: True

greedy2.py

@@ -11,7 +11,7 @@ def __init__(self, config):
         self.sk = my_sk(config) 
         self.logfile = os.path.join('output', 
                                     self.sk.time_str+'_hlog.txt')
-        log_str = 'Instance: {}'.format(self.sk.instance_name)
+        log_str = 'Instance: {}'.format(self.sk.instance_str)
         log_str += '\nProblem parameters: \n{} vehicles'.format(
                     len(range(self.sk.vehicle_data.shape[0])))
         log_str += '\n{} consumers\n{} producers'.format(

paper.py

@@ -0,0 +1,67 @@
+# execute python file
+
+import os
+import glob
+import logging
+from sys import platform
+import yaml
+
+from utils import *
+from smart_krit import my_sk
+
+
+# Read configs
+if platform in ['linux','linux2']:
+    configs = glob.glob(os.path.join('configs', '*.YAML')) +  glob.glob(os.path.join('configs', '*.yaml'))
+elif platform == 'win32':
+    configs = glob.glob(os.path.join('configs', '*.YAML'))
+else:
+    print('Unknown platform!')
+    exit()
+
+# logging
+# TODO:
+
+
+for config in configs:
+    with open(config) as config_file:
+        yaml_dict = yaml.load(config_file,
+                              Loader=yaml.FullLoader)
+    print(f'Config file: {config}')
+
+    for t in [2.0, 3.0, 4.0, 5.0, 10.0]:
+        # Part B: objective 0
+        yaml_dict['objective'] = 0
+        yaml_dict['T'] = t
+        best_limit = None
+        best_res = None
+        for v_limit in [40, 30, 20, 15, 10, 5, 4, 3, 2, 1]:
+            print(f'Limit: {v_limit}')
+            yaml_dict['constrain_vehicles'] = v_limit
+            sk = my_sk(yaml_dict)
+            sk.preprocess()
+            grb_mod = sk.solve()
+            sk.postprocess(grb_mod)
+
+            # Check feasibility
+            if grb_mod.status == 2:
+                best_limit = v_limit
+                best_res = sk.instance_str + '.txt'
+                print('Feasible')
+            else:
+                print('Infeasible')
+
+        print(f'Finished part B: Best Limit: {v_limit} in file {best_res}')
+        #exit()
+
+        # Part C: warm-start with remaining time
+        yaml_dict['constrain_vehicles'] = best_limit
+        yaml_dict['objective'] = 1
+        sk = my_sk(yaml_dict)
+        sk.preprocess()
+        w, s_n, s_v, f, z, e = read_results(os.path.join('output', best_res))
+        grb_mod = sk.solve(w_start=w, s_n_start=s_n, s_v_start=s_v,
+                           f_start=f, z_start=z, e_start=e)
+        sk.postprocess(grb_mod)
+
+    exit()

smart_krit.py

@@ -9,15 +9,22 @@
 
 class my_sk():
     def __init__(self, config):
+        '''
+        config: path to YAML or yaml_dict
+        '''
         # create output folder and read config
         if not os.path.exists('output'):
             os.makedirs('output')
         self.time_str = datetime.now().strftime("%m_%d-%H_%M_%S")
-        with open(config) as config_file:
-            yaml_dict = yaml.load(config_file, 
-                                  Loader=yaml.FullLoader)
-        base_name = os.path.basename(config)
-        self.instance_name = os.path.splitext(base_name)[0]
+
+        if isinstance(config, str):
+            with open(config) as config_file:
+                yaml_dict = yaml.load(config_file, 
+                                    Loader=yaml.FullLoader)
+            # base_name = os.path.basename(config)
+            # self.instance_name = os.path.splitext(base_name)[0]
+        elif isinstance(config, dict):
+            yaml_dict = config
 
         # model settings
         self.obj = yaml_dict['objective']