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Implement greedy solution. Reaches 35/80, 56 needed to pass.

main
Felix Martin 2020-01-05 20:48:51 -05:00
parent 42611d79a5
commit 590e6713d1
3 changed files with 209 additions and 6 deletions
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204
facility/facility.py Executable file
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@ -0,0 +1,204 @@
#!/usr/bin/env python3
import math
from collections import namedtuple
Point = namedtuple("Point", ['x', 'y'])
Facility = namedtuple("Facility", ['index', 'setup_cost', 'capacity', 'location'])
Customer = namedtuple("Customer", ['index', 'demand', 'location'])
class Solution(object):
def __init__(self, facilities, customers):
self.facilities = facilities
self.customers = customers
self.cost = 0
self.facility_connected_customers = [set() for _ in facilities]
self.facility_remaining_capacity = [f.capacity for f in facilities]
self.customer_to_facility = [None for _ in customers]
def connect(self, customer_index, facility_index):
customer = self.customers[customer_index]
facility = self.facilities[facility_index]
# If customers is already connected handle disconnect properly.
if (connected_facitlity_index := self.customer_to_facility[customer_index]):
self.disconnect(customer_index, connected_facitlity_index)
# If facility is currently not used we have to set it up.
if not self.facility_connected_customers[facility_index]:
self.cost += facility.setup_cost
self.facility_connected_customers[facility_index].add(customer_index)
if self.facility_remaining_capacity[facility_index] < customer.demand:
raise Exception(f"Cannot connect {customer} to {facility}.")
self.facility_remaining_capacity[facility_index] -= customer.demand
self.customer_to_facility[customer_index] = facility_index
self.cost += length(facility.location, customer.location)
def disconnect(self, customer_index, facility_index):
customer = self.customers[customer_index]
facility = self.facilities[facility_index]
self.cost -= length(facility.location, customer.location)
self.facility_connected_customers[facility_index].remove(customer_index)
self.facility_remaining_capacity[facility_index] += customer.demand
self.customer_to_facility[customer_index] = None
if not self.facility_connected_customers[facility_index]:
self.cost -= self.facilities[facility_index].setup_cost
def get_feasible_facilities(self, customer_index):
customer = self.customers[customer_index]
facility_indices = [f.index
for f in self.facilities
if self.facility_remaining_capacity[f.index] >= customer.demand]
if not facility_indices:
raise Exception("No feasible facilities.")
def key(facility_index):
cost = 0
facility = self.facilities[facility_index]
# If there are customers yet we have to open it.
if not self.facility_connected_customers[facility_index]:
cost += facility.setup_cost
cost += length(customer.location, facility.location)
return cost
facility_indices.sort(key=key)
return facility_indices
def is_valid(self):
for customer in self.customers:
if self.customer_to_facility[customer.index] is None:
raise Exception(f"{customer} not connected.")
for facility in self.facilities:
if self.facility_remaining_capacity[facility.index] < 0:
raise Exception(f"{facility} exceeds capacity.")
cost = sum([f.setup_cost
for f in self.facilities
if self.facility_connected_customers[f.index]])
for customer in self.customers:
facility = self.facilities[self.customer_to_facility[customer.index]]
cost += length(facility.location, customer.location)
if abs(cost - self.cost) > 0.00001:
raise Exception(f"Running cost {self.cost} unequal to actual cost {cost}.")
return True
def plot_map(self):
try:
import matplotlib.pyplot as plt
import matplotlib.lines as lines
except ModuleNotFoundError:
return
figure = plt.figure()
for f in self.facilities:
x, y = f.location
color = 'ro' if self.facility_connected_customers[f.index] else 'go'
plt.plot(x, y, color)
rem_cap = self.facility_remaining_capacity[f.index]
plt.text(x, y, f" F({f.index}, {f.setup_cost}, {rem_cap}/{f.capacity})")
for c in self.customers:
x, y = c.location
plt.plot(x, y, 'bx')
plt.text(x, y, f" C({c.index}, {c.demand})")
if (f_index := self.customer_to_facility[c.index]) is not None:
f = self.facilities[f_index]
x_f, y_f = f.location
plt.plot([x, x_f], [y, y_f], 'b-')
plt.show()
def get_facilities_by_customers(self):
facility_indices = [f.index for f in self.facilities
if self.facility_connected_customers[f.index]]
def key(facility_index):
return len(self.facility_connected_customers[facility_index])
facility_indices.sort(key=key)
return facility_indices
def to_output_data(self):
# calculate the cost of the solution
self.is_valid()
obj = self.cost
# prepare the solution in the specified output format
output_data = '%.2f' % obj + ' ' + str(0) + '\n'
output_data += ' '.join(map(str, self.customer_to_facility))
return output_data
def length(point1, point2):
return math.sqrt((point1.x - point2.x)**2 + (point1.y - point2.y)**2)
def build_trivial_solution(solution):
# build a trivial solution
# pack the facilities one by one until all the customers are served
facility_index = 0
for customer in solution.customers:
if solution.facility_remaining_capacity[facility_index] >= customer.demand:
solution.connect(customer.index, facility_index)
else:
facility_index += 1
solution.connect(customer.index, facility_index)
return solution
def build_greedy_solution(solution):
for customer in solution.customers:
facility_index = solution.get_feasible_facilities(customer.index)[0]
solution.connect(customer.index, facility_index)
return solution
def solve_it(input_data):
facilities, customers = parse(input_data)
solution = Solution(facilities, customers)
build_greedy_solution(solution)
solution.plot_map()
output_data = solution.to_output_data()
return output_data
def main():
file_location = "data/fl_3_1"
with open(file_location, 'r') as input_data_file:
input_data = input_data_file.read()
print(solve_it(input_data))
def parse(input_data):
# parse the input
lines = input_data.split('\n')
parts = lines[0].split()
facility_count = int(parts[0])
customer_count = int(parts[1])
facilities = []
for i in range(1, facility_count+1):
parts = lines[i].split()
facilities.append(Facility(i-1, float(parts[0]), int(parts[1]),
Point(float(parts[2]), float(parts[3])) ))
customers = []
for i in range(facility_count+1, facility_count+1+customer_count):
parts = lines[i].split()
customers.append(Customer(i-1-facility_count, int(parts[0]),
Point(float(parts[1]), float(parts[2]))))
return facilities, customers
if __name__ == "__main__":
main()

7
facility/solver.py
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@ -2,6 +2,7 @@
# -*- coding: utf-8 -*-
from collections import namedtuple
from facility import solve_it
import math
Point = namedtuple("Point", ['x', 'y'])
@ -11,7 +12,7 @@ Customer = namedtuple("Customer", ['index', 'demand', 'location'])
def length(point1, point2):
return math.sqrt((point1.x - point2.x)**2 + (point1.y - point2.y)**2)
def solve_it(input_data):
def solve_it_example(input_data):
# Modify this code to run your optimization algorithm
# parse the input
@ -20,7 +21,7 @@ def solve_it(input_data):
parts = lines[0].split()
facility_count = int(parts[0])
customer_count = int(parts[1])
facilities = []
for i in range(1, facility_count+1):
parts = lines[i].split()
@ -63,8 +64,6 @@ def solve_it(input_data):
return output_data
import sys
if __name__ == '__main__':
import sys
if len(sys.argv) > 1:

4
facility/submit.py
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@ -214,7 +214,7 @@ def output(input_file, solver_file):
solution = ''
start = time.clock()
start = time.process_time()
try:
solution = pkg.solve_it(load_input_data(input_file))
except Exception as e:
@ -224,7 +224,7 @@ def output(input_file, solver_file):
print(str(e))
print('')
return 'Local Exception =('
end = time.clock()
end = time.process_time()
if not (isinstance(solution, str) or isinstance(solution, unicode)):
print('Warning: the solver did not return a string. The given object will be converted with the str() method.')