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scp_crane.py
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scp_crane.py
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from gurobipy import *
import pandas as pd
DEBUG = False
def solve_scp(demand_points_df, supply_points_df, crane_locs_df, cranes_df, filestr, phasedict, verbose = False):
crane_ids = list(cranes_df['ind'].unique())
loc_ids = list(crane_locs_df['ind'].unique())
crane_list = cranes_df.to_dict(orient = 'split')['data']
loc_list = crane_locs_df.to_dict(orient = 'split')['data']
if verbose: print('Reading data..', end = '')
kl_dict = {
crane_id: {
'loc_ids': {
loc_id: {
'x': 0,
'y': 0,
'z': 0,
} for loc_id in loc_ids
},
'max_r': 0,
'height': 0,
'max_moment': 0,
'cost': 0,
'fixed': 0,
'phases': None
} for crane_id in crane_ids
}
for crane in crane_list:
crane_id = crane[cranes_df.columns.get_loc('ind')]
max_r = crane[cranes_df.columns.get_loc('maxR')]
max_moment = crane[cranes_df.columns.get_loc('max_moment')]
height = crane[cranes_df.columns.get_loc('Ht')]
crane_phases = crane[cranes_df.columns.get_loc('Phase')]
cost = crane[cranes_df.columns.get_loc('Cost')]
fixed = crane[cranes_df.columns.get_loc('Fixed')]
kl_dict[crane_id]['max_r'] = max_r
kl_dict[crane_id]['max_moment'] = max_moment
kl_dict[crane_id]['height'] = height
kl_dict[crane_id]['phases'] = crane_phases
kl_dict[crane_id]['cost'] = cost
kl_dict[crane_id]['fixed'] = fixed
for loc in loc_list:
loc_id = loc[crane_locs_df.columns.get_loc('ind')]
x = loc[crane_locs_df.columns.get_loc('X')]
y = loc[crane_locs_df.columns.get_loc('Y')]
z = loc[crane_locs_df.columns.get_loc('Z')]
loc_phases = loc[crane_locs_df.columns.get_loc('Phase')]
assert loc_phases == crane_phases, f'Diff phases provided!'
kl_dict[crane_id]['loc_ids'][loc_id]['x'] = x
kl_dict[crane_id]['loc_ids'][loc_id]['y'] = y
kl_dict[crane_id]['loc_ids'][loc_id]['z'] = z
if verbose: print('Done')
if DEBUG: print(kl_dict)
def pass_supply(loc, maxR, phases):
xyz = (supply_points_df['X'].astype(float) - loc['x']) ** 2 + (supply_points_df['Y'].astype(float) - loc['y']) ** 2 < maxR ** 2
phase = supply_points_df['Phase'].apply(lambda sp: any(p in sp for p in phases))
return any(xyz & phase)
# Check supply constraints
if verbose: print('Checking supply constraints..', end = '')
kls_dict = {
crane_id: {
'loc_ids': {
loc_id: kl_dict[crane_id]['loc_ids'][loc_id] for loc_id in loc_ids \
if pass_supply(kl_dict[crane_id]['loc_ids'][loc_id], kl_dict[crane_id]['max_r'], kl_dict[crane_id]['phases'])
},
'max_r': kl_dict[crane_id]['max_r'],
'height': kl_dict[crane_id]['height'],
'max_moment': kl_dict[crane_id]['max_moment'],
'cost': kl_dict[crane_id]['cost'],
'fixed': kl_dict[crane_id]['fixed'],
'phases': kl_dict[crane_id]['phases']
} for crane_id in kl_dict.keys()
}
if verbose: print('Done')
if DEBUG: print(kls_dict)
if verbose:
prev_len = sum([len(v['loc_ids']) * len(list_powerset(v['phases'])[1:]) for v in kl_dict.values()])
new_len = sum([len(v['loc_ids']) * len(list_powerset(v['phases'])[1:]) for v in kls_dict.values()])
print(f'Removed {(prev_len - new_len)} crane-loc-phases that fail supply constraints')
def passed_demand_points(loc, maxR, height, max_moment, phase):
"""
:param loc: dict of {x, y, z}
:param phase: a str of phases
"""
c_sq = [(dx - loc['x']) ** 2 + (dy - loc['y']) ** 2 \
for dx, dy in zip(demand_points_df['X'], demand_points_df['Y'])]
pass_dist = [dist < maxR ** 2 for dist in c_sq]
pass_height = [loc['z'] + height >= dz for dz in demand_points_df['Z']]
pass_moment = [dist * v <= max_moment for dist, v in zip(c_sq, demand_points_df['Vol'])]
pass_phase = [any(p in dp for p in phase) for dp in demand_points_df['Phase']]
return [d and h and m and p for d, h, m, p in zip(pass_dist, pass_height, pass_moment, pass_phase)]
# Check demand and moment constraints
if verbose: print('Checking demand, moment and phase constraints..', end = '')
klsd_dict = {
crane_id: {
'loc_ids': {loc_id: {
phase: passed_demand_points(kls_dict[crane_id]['loc_ids'][loc_id], kls_dict[crane_id]['max_r'], \
kls_dict[crane_id]['height'], kls_dict[crane_id]['max_moment'], phase) \
for phase in kls_dict[crane_id]['phases']
} for loc_id in kls_dict[crane_id]['loc_ids'].keys()
},
'cost': kls_dict[crane_id]['cost'],
'fixed': kls_dict[crane_id]['fixed'],
'phases': kls_dict[crane_id]['phases']
} for crane_id in kls_dict.keys()
}
if verbose: print('Done')
if DEBUG: print(klsd_dict)
if verbose:
prev_len = sum([len(v['loc_ids']) * len(list_powerset(v['phases'])[1:]) for v in kls_dict.values()])
new_len = sum([len(v['loc_ids']) * len(list_powerset(v['phases'])[1:]) for v in klsd_dict.values()])
print(f'Removed {(prev_len - new_len)} crane-loc-phases that fail demand constraints')
def union_phases(demand_flags, phases):
"""
Returns union of demand_flags according to phases
:param demand_flags: dict of list of boolean flags for crane-loc {phase: [True or False]}
:param phases: list of phases to union demand_flags on
"""
if len(phases) == 1:
return demand_flags[phases[0]]
union = demand_flags[phases[0]]
for phase in phases[1:]:
union = [e1 or e2 for e1, e2 in zip(union, demand_flags[phase])]
return union
# Check phase constraint
if verbose: print('Taking powerset of phases..', end = '')
klsdp_dict = {
crane_id: {
'loc_ids': {
loc_id: {
''.join(phase): union_phases(klsd_dict[crane_id]['loc_ids'][loc_id], phase) \
for phase in list_powerset(klsd_dict[crane_id]['phases'])[1:]
} for loc_id in klsd_dict[crane_id]['loc_ids'].keys()
},
'cost': klsd_dict[crane_id]['cost'],
'fixed': klsd_dict[crane_id]['fixed'],
} for crane_id in klsd_dict.keys()
}
if verbose: print('Done')
if DEBUG: print(klsdp_dict)
if verbose:
passed = sum(
[sum(
[sum(
[sum(
klsdp_dict[k]['loc_ids'][l][p]) for p in klsdp_dict[k]['loc_ids'][l].keys()]) \
for l in klsdp_dict[k]['loc_ids'].keys()]) \
for k in klsdp_dict.keys()]
)
print(f'Total valid crane-loc-phases: {passed}')
if verbose: print('Binarizing boolean values..', end = '')
def binarize(l):
"""
Converts list of boolean to list of 1's and 0's
"""
return [1 if e else 0 for e in l]
kl_model = {
crane_id: {
loc_id: {
phase: binarize(klsdp_dict[crane_id]['loc_ids'][loc_id][phase]) \
for phase in klsdp_dict[crane_id]['loc_ids'][loc_id].keys()
} for loc_id in klsdp_dict[crane_id]['loc_ids'].keys()
} for crane_id in klsdp_dict.keys()
}
if verbose: print('Done')
m = Model("SCP")
if verbose: print('Computing costs..', end = '')
krane = []
total_cost = []
A = []
for crane_id, d1 in klsdp_dict.items():
cost = d1['cost']
fixed = d1['fixed']
for loc_id, d2 in d1['loc_ids'].items():
for phase, demand_flags in d2.items():
klstr = loc_id + '_' + crane_id + '_' + ''.join(phase) + '_' + str(len(krane))
krane.append(m.addVar(lb = 0.0, ub = 1.0, vtype = GRB.BINARY, name = klstr))
total_cost.append(calc_cost1(cost, fixed, phase, phasedict))
A.append(demand_flags)
if verbose: print('Done\nAdding constraints..', end = '')
if DEBUG: print(len(A))
m.update()
for i in range(len(A[0])):
expr = LinExpr()
for j in range(len(A)):
if A[j][i] != 0:
expr += A[j][i] * krane[j]
m.addConstr(expr, GRB.GREATER_EQUAL, 1)
m.setObjective(quicksum(krane[i] * total_cost[i] for i in range(len(krane))), GRB.MINIMIZE)
if verbose: print('Done\nStart optimize..', end = '')
m.optimize()
if verbose: print('Done')
m.write(filestr)
def list_powerset(lst):
# the power set of the empty set has one element, the empty set
result = [[]]
for x in lst:
result.extend([subset + [x] for subset in result])
return result
def calc_cost1(klcost, klfixed, klphase, phasedict):
# Predefined: Length of Phases a, b, c etc. Undefined phases are 'free'.
# phasedict is a dictionary with the following: {'a':duration of a, 'b':duration of b, 'c':duration of c}
cost = 0
for i, j in phasedict.items():
if nested(i, klphase):
cost += klcost * j
'''
if nested('a', klphase):
cost += klcost * 7 # phase a takes 4 weeks... klcost is cost per week
if nested('b', klphase):
cost += klcost * 11 # phase b takes 8 weeks... klcost is cost per week
if nested('c', klphase):
cost += klcost * 33
'''
# to determine number of times to install and dismantle: take the difference of two lists. Each list converted into
# a set to make each element unique. The first list is the total number of phases available: [a, b, c, d] etc.
# Subtract the two lists, and find the length of the new list. Add one to the len of this list to get number of
# install or dismantle.
original_schedule = ['a', 'b', 'c'] # remember to change this as well... use this for ABC, ACB, BAC, BCA, CBA, CAB
#original_schedule = list(phasedict.keys()) # this has some error. dictionary has no order. So it keeps jumping around.
start = original_schedule.index(klphase[0])
stop = original_schedule.index(klphase[-1])
trunc_sched = original_schedule[start:stop + 1]
multiples = len(list(set(trunc_sched) - set(klphase))) + 1
cost += multiples * klfixed
return cost
# Nice code for checking if an element exists in a nested list... which is what is potentially possible in klphase
def flatten(lst):
for elem in lst:
if isinstance(elem, (list, tuple)):
for nested in flatten(elem):
yield nested
else:
yield elem
def nested(x, ys):
return any(x == nested for nested in flatten(ys))