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Data.py
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import numpy as np
objectives_penalizado = [1000000000,0,0]
# ADCS: id nombre costo masa vol confiabilidad potencia
ADCS = np.array([
[1, "iMTQ_Magnetorquer_Board", 9600, 0.196, 0.17, 0.98, 1.2],
[2, "IADCS-100", 120000, 0.4, 0.32, 0.98, 1.15],
])
# COM: id nombre costo masa vol confiabilidad potencia
COM = np.array([
[1, "kit_isis", 11880, 0.164, 0.18, 0.98, 5.8],
[2, "PULSAR-TMTC", 10823, 0.1, 0.1651, 0.995, 4.25],
[3, "PULSAR-DATA", 17174, 0.1, 0.1741, 0.995, 5],
])
# EPS: id nombre costo masa vol confiabilidad potencia
EPS = np.array([
[1, "isis_eps_a", 5520, 0.184, 0.26, 0.98, 32],
[2, "isis_eps_b", 9600, 0.31, 0.21, 0.98, 64],
[3, "isis_eps_c", 12000, 0.36, 0.21, 0.98, 64],
[4, "modular_eps", 23760, 0.4161, 0.54, 0.995, 39],
[5, "starbuck-nano-photon", 10934, 0.221, 0.162, 0.995, 60],
])
# OBC: id nombre costo masa vol confiabilidad potencia
OBC = np.array([
[1, "ISIS_On_Board_Computer", 5280, 0.094, 0.124, 0.98, 0.4],
[2, "KRYTEN-M3", 8624, 0.0619, 0.0551, 0.995, 0.6],
[3, "SIRIUS_OBC_LEON3FT", 23285, 0.13, 0.0551, 0.995, 1.3],
[4, "SIRIUS_TMC_LEON3FT", 32340, 0.13, 0.1720, 0.995, 1.3],
])
# STR: id costo U(factor) confiabilidad
STR = np.array([
[1, 2580, 1, 0.98],
[2, 3870, 1.5, 0.98],
[3, 3540, 2, 0.98],
[4, 3780, 2, 0.98],
[5, 4380, 3, 0.98],
[6, 6960, 4, 0.98],
[7, 8820, 6, 0.98],
[8, 11400, 8, 0.98],
])
# PL: id nombre costo masa volumen confiabilidad potencia
PL_list = np.array([
[1, "gecko", 31680, 0.40, 0.65, 0.98, 2.70],
[2, "chameleon", 224280, 1.60, 2.15, 0.98, 7.00],
[3, "mantis", 68280, 0.50, 0.65, 0.98, 4.50],
[4, "piCAM-FM", 3948, 0.1, 0.19, 0.98, 0.297],
[5, "caiman", 140280, 1.8, 2.65, 0.98, 10],
[6, "TriScape_100", 48000, 1.1, 1.76, 0.985, 6],
[7, "HyperScape_100", 182400, 1.2, 1.76, 0.985, 5.5],
[8, "ThermoVision_A10", 400, 0.12, 0.4826, 0.9, 1.5],
[9, "Tau_320", 1300, 0.479, 0.2921, 0.9, 1],
[10, "Vacio", 0, 0, 0, 1, 0],
])
# GSD[LR,MR,HR]
GSD = np.array([
[0, 1, 0],
[0, 1, 0],
[0, 1, 0],
[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[0, 0, 1],
[1, 0, 0],
[1, 0, 0],
[0, 0, 0],
])
# RE[UV,VIS,NIR,SWIR,MWIR,TIR,MW]
RE = np.array([
[0, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
])
# Rentabilidad
RENT = np.array([
[0, 0, 0, 8, 0, 0, 0],
[0, 0, 0, 16, 0, 24, 0],
[0, 0, 0, 28, 0, 42, 0],
[12, 20, 8, 8, 0, 0, 10],
[21.6, 36, 14.4, 14.4, 18, 21.6, 18],
[36, 60, 14.4, 24, 30, 36, 30],
[13.2, 0, 8.8, 8, 0, 0, 10],
[19.2, 0, 16, 12.8, 0, 19.2, 16],
[42, 0, 16, 28, 0, 42, 35],
[12, 20, 0, 8, 0, 0, 10],
[26.4, 44, 0, 17.6, 0, 0, 22],
[43.2, 72, 0, 28.8, 0, 0, 36],
[0, 0, 0, 8, 0, 0, 10],
[0, 0, 0, 19.2, 0, 0, 24],
[0, 0, 0, 28.8, 0, 0, 36],
[0, 0, 12.8, 0, 0, 0, 10],
[0, 0, 20, 0, 25, 30, 25],
[0, 0, 20, 0, 38, 45.6, 38],
[24, 0, 0, 0, 0, 0, 20],
[48, 0, 0, 0, 40, 48, 40],
[72, 0, 0, 0, 60, 72, 60],
])
costo_fijo=8000