KuMiShi/Optim_Metaheuristique
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updating mopso.py

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Amimine
2026-01-18 14:50:26 +01:00
parent 76cd66c00d
commit 0dd6770457
1 changed files with 3 additions and 3 deletions
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mopso.py
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@@ -1,5 +1,5 @@
import random as rd import random as rd
from .particle import Particle from particle import Particle
import copy import copy
class MOPSO(): class MOPSO():
@@ -17,7 +17,7 @@ class MOPSO():
# Initialisation of particle's global parameters # Initialisation of particle's global parameters
self.A_max = A_max # Network's power limit self.A_max = A_max # Network's power limit
self.socs, self.socs_req = self.generate_state_of_charges(nb_vehicles,nb_of_ticks) self.socs, self.socs_req = self.generate_state_of_charges(nb_vehicles,nb_of_ticks)
self.times = self.generate_times(nb_vehicles, nb_of_ticks, delta_t) self.times = self.generate_times(nb_vehicles, nb_of_ticks)
self.prices = self.generates_prices(nb_of_ticks,price_mean,price_std) #TODO: Use RTE France prices for random prices generation according to number of ticks self.prices = self.generates_prices(nb_of_ticks,price_mean,price_std) #TODO: Use RTE France prices for random prices generation according to number of ticks
self.capacities = capacities self.capacities = capacities
@@ -83,7 +83,7 @@ class MOPSO():
def generates_prices(self,nb_of_ticks:int, mean:float, std:float): def generates_prices(self,nb_of_ticks:int, mean:float, std:float):
prices = [] prices = []
for _ in range(nb_of_ticks): for _ in range(nb_of_ticks):
variation = rd.randrange(-(std*10), (std * 10) +1, 1) / 10 # Random float variation variation = rd.uniform(-std, std) # Random float variation
prices.append(mean + variation) prices.append(mean + variation)
return prices return prices