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Genetic_Algorithm setup but ??
Genetic_Algorithm setup but ??
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‎src/Genetic_Algorithm.py‎

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# Implementasi Algoritma Penjadwalan Genetic-Algorithm
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# 1. Impor modul eksternal
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import csv
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# 2. Definisi variabel global
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ROUTING = []
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PROCESSING_TIME = []
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MESIN = []
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JOB_DONE = []
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SCHEDULE = []
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# 3. Prosedur untuk melakukan pembacaan data dari file
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def read_data():
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# Menggunakan variabel global
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global ROUTING, PROCESSING_TIME, MESIN
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print("Sedang membaca data...")
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# Pembacaan data mesin dari file dan exception handling
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try:
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mesin_file = open(f"test3/Mesin.txt", "r")
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except:
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print(f"File Mesin.txt tidak ditemukan!")
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exit()
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# Konversi ke tabel
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mesin_data = csv.reader(mesin_file)
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# Pengolahan isi tabel
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for row in mesin_data:
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for i in range(len(row)):
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row[i] = float(row[i])
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if row[i] % 1.0 == 0:
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row[i] = int(row[i])
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MESIN.append(row)
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print("Data mesin berhasil dibaca!")
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# Pembacaan data job dari file
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n_jobs = int(input("Masukkan jumlah job: "))
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for j in range(n_jobs):
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# Exception handling
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try:
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time_file = open(f"test3/Job{j + 1}_Time.txt", "r")
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except:
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print(f"File Job{j + 1}_Time.txt tidak ditemukan!")
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exit()
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# Konversi ke tabel
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time_data = csv.reader(time_file)
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# Pengolahan isi tabel
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for row in time_data:
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for i in range(len(row)):
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row[i] = float(row[i])
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if row[i] % 1.0 == 0:
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row[i] = int(row[i])
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PROCESSING_TIME.append(row)
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# Exception handling
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try:
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routing_file = open(f"test3/Job{j + 1}_Routing.txt", "r")
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except:
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print(f"File Job{j + 1}_Routing.txt tidak ditemukan!")
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exit()
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# Konversi ke tabel
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routing_data = csv.reader(routing_file)
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# Pengolahan isi tabel
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for row in routing_data:
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for i in range(len(row)):
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row[i] = float(row[i])
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if row[i] % 1.0 == 0:
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row[i] = int(row[i])
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ROUTING.append(row)
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print("Data time dan routing berhasil dibaca!")
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# 4. Prosedur Eksekusi
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def do_genetic_algo():
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# xx. Menggunakan variabel global
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global MESIN, JOB_DONE, SCHEDULE, CJ, TJ, RJ, ST
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# a. Mengambil nilai cj terkecil dari data masukan, job dengan cj terkecil akan diproses duluan
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min_c = min(CJ)
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# b. Inisiasi senarai temporari
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temp_list = []
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# c. Kalau misal ada lebih dari 1 yang punya nilai minimum, digunakan skema penanganan
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if CJ.count(min_c) > 1:
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# Inisiasi senarai yang berisi semua job dengan nilai min_c
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index_c_in_cj = [i for i in range(len(CJ)) if CJ[i] == min_c]
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# Cek nilai rj dan pilih yang mempunyai nilai rj terkecil
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# Prioritaskan yang jumlah operasinya masih banyak
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machine_list = [] # machine list
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# Isi list dengan semua data yang ada di index_c_in_cj
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for i in index_c_in_cj:
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# Kalau belum ada di machine list, tambahkan
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if len(temp_list) == 0 or ST[i][2] not in machine_list:
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temp_list.append(ST[i])
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machine_list.append(ST[i][2])
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# print("masuk sini?", ST[i][2])
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print("i, stvals", i, ST[i][2])
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mach_on_ST = []
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# print("ST", ST)
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for k in range (len(ST)):
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mach_on_ST.append(ST[k][2])
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k = mach_on_ST.index(ST[i][2])
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MESIN[0][ST[i][2] - 1] = RJ[k]
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print("ST", ST)
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# Kalau sudah ada, lakukan filtering sesuai kriteria diatas
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elif ST[i][2] in machine_list:
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index_mac = machine_list.index(ST[i][2])
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job = ST[i][0]
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# Kalo mesinnya kosong, atau bisa selesai lebih cepat, masukin di
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# tempat yang memungkinkan, proses genetikasi
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if (ST[i][2] >= 1 and ST[i][2] <= 4):
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minimum = MESIN[0][0]
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idx_mesin = 0
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for j in range (4):
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if (minimum > MESIN[0][j]):
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idx_mesin = j
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minimum = MESIN[0][j]
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if (MESIN[0][ST[i][2] - 1] > minimum):
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ST[job-1] = [job, ST[job-1][1], idx_mesin + 1]
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temp_list.append(ST[job-1])
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print ("ST", ST)
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elif (ST[i][2] >= 5 and ST[i][2] <= 6):
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minimum = MESIN[0][4]
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idx_mesin = 0
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for j in range (4, 5):
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if (minimum > MESIN[0][j]):
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idx_mesin = j
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minimum = MESIN[0][j]
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if (MESIN[0][ST[i][2] - 1] > minimum):
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ST[i] = [job, ST[i][1], idx_mesin + 1]
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temp_list.append(ST[i])
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else :
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# Prioritas nilai rj
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if (RJ[i] < RJ[ST.index(temp_list[index_mac])]):
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temp_list[index_mac] = ST[i]
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# Prioritas jumlah operasi
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elif ST[i][1] < temp_list[index_mac][1]:
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temp_list[index_mac] = ST[i]
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MESIN[0][ST[i][2] - 1] = RJ[ST[i][2] - 1]
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# Sekarang temp_list isinya job yang mau dijalankan (dalam sebuah list)
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retval = temp_list
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# Kalau tidak, kembalikan saja nilai st dari cj tersebut dalam sebuah list
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else:
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retval = [ST[CJ.index(min_c)]]
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# d. Melakukan indexing terhadap jadwal yang ada dan telah selesai
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print("retval?", retval)
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job = []
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instance = []
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machine = []
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for i in range (len(retval)):
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job.append(retval[i][0])
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instance.append(retval[i][1])
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machine.append(retval[i][2])
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print("job, retval", job, machine)
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job_on_ST = []
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# print("ST", ST)
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for i in range (len(ST)):
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job_on_ST.append(ST[i][0])
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print("job_on_st", job_on_ST)
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for value in job:
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i = job_on_ST.index(value)
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print("i", i)
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SCHEDULE.append([ST[i][0], ST[i][1], ST[i][2], CJ[i], RJ[i]])
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if ST[i][1] == len(ROUTING[ST[i][0] - 1]):
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JOB_DONE.append([ST[i][0], RJ[i]])
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# e. Lanjutan pemrosesan indexing untuk dikemas dalam senarai job dan machine
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index_job = [job_on_ST.index(value) for value in job]
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index_mac = machine
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# f. Melakukan penyalinan nilai st dan cj untuk digunakan lebih lanjut pada bagian bawah
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COPY_OF_ST = [i for i in ST]
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COPY_OF_CJ = [i for i in CJ]
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# g. Melakukan perubahan terhadap nilai isi mesin, tj dan st
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# bias untuk membantu skema penghapusan berdasar indeks
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bias = 0
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for i, j in zip(index_job, index_mac):
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# Memperbaharui nilai MESIN
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# MESIN[0][j] = RJ[i]
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try:
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# Memperbaharui nilai tj
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TJ[i] = PROCESSING_TIME[ST[i][0] - 1][ST[i][1]]
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# Memperbaharui nilai st
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ST[i] = [ST[i][0], ST[i][1] + 1, ROUTING[ST[i][0] - 1][ST[i][1]]]
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except:
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# Exception handling jika tidak ada, maka saatnya dihapus
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TJ.pop(i - bias)
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ST.pop(i - bias)
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CJ.pop(i - bias)
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bias += 1
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# h. Memperbaharui nilai cj pada COPY_OF_CJ (salinan cj)
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for i in range(len(COPY_OF_ST)):
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try:
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# Jika nilai iterator berada pada index_job,
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# maka update dengan nilai data proses selanjutnya, lakukan perbandingan dengan
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# nilai proses pada mesin
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if i in index_job:
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ready_time = MESIN[0][ST[i][2] - 1]
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recent_rjx = RJ[i]
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if COPY_OF_ST[i][1] != len(ROUTING[COPY_OF_ST[i][0] - 1]):
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if ready_time > recent_rjx:
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COPY_OF_CJ[i] = ready_time
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else :
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COPY_OF_CJ[i] = recent_rjx
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# Jika tidak ada, lakukan pembaharuan dengan nilai yang ada di mesin
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# Mengingat tidak ada job yang saling overlap
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else :
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if (COPY_OF_CJ[i] <= MESIN[0][COPY_OF_ST[i][2] - 1]):
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COPY_OF_CJ[i] = MESIN[0][COPY_OF_ST[i][2] - 1]
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except:
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# Exception handling, skip jika tidak memenuhi kondisi diatas
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continue
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# i. Pembahruan terhadap nilai cj berdasar pemrosesan COPY_OF_CJ dan COPY_OF_ST
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# dilakukan hanya jika panjang keduanya sudah beda (akibat proses penghapusan)
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if (len(CJ) < len(COPY_OF_CJ)):
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for i in range(len(COPY_OF_CJ) - 1, -1, -1):
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# Proses penyesuaian dengan cj yang sudah baru dengan menghapus
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if i in index_job and COPY_OF_ST[i][1] == len(ROUTING[COPY_OF_ST[i][0] - 1]):
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COPY_OF_CJ.pop(i)
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else :
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continue
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# Penyalinan kembali nilai cj yang telah diperbaharui
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CJ = COPY_OF_CJ
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print("fin cj", CJ)
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# j. Pembaharuan terhadap nilai rj
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RJ = [0 for i in range(len(ST))]
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for i in range (len(ST)):
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RJ[i] = CJ[i] + TJ[i]
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# k. Pengembalian nilai ST apakah sudah kosong (semua job sudah diproses)
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return ST
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# 5. Melakukan pencetakan form hasil pemrosesan ke terminal
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def print_schedule(schedule=SCHEDULE, lateness=None):
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global PROCESSING_TIME
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makespan = max(schedule, key=lambda x: x[4])[4]
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for i in range(len(PROCESSING_TIME)):
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j = max(filter(lambda a: a[0] == i + 1, schedule), key=lambda x: x[4])[4]
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print(f'Job {i + 1} telah selesai dengan waktu selesai {round(j,2)}')
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for s in sorted(schedule, key=lambda x: x[0]):
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if s[0] == i + 1:
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print(f'{s[0]}{s[1]}{s[2]}: Start {round(s[3],2)} End {round(s[4],2)}')
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if lateness is not None:
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print(f"Earliness: {round(lateness[i],2) * -1}" if lateness[i] <= 0 else f"Tardiness: {round(lateness[i],2)}")
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print(f'---\nmakespan: {round(makespan,2)}')
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# 6. Program utama
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if __name__ == '__main__':
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# xx. Membaca data
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read_data()
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# a. Mendefinisikan posisi melalui routing
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CJ = [MESIN[0][ROUTING[i][0] - 1] for i in range(len(ROUTING))]
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# b. Mendefinisikan waktu pemrosesan
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TJ = [PROCESSING_TIME[i][0] for i in range(len(ROUTING))]
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# c. Mendefinisikan waktu berakhir
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RJ = [0 for i in range(len(ROUTING))]
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for i in range (len(ROUTING)):
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RJ[i] = CJ[i] + TJ[i]
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# d. Mendefinisikan id st (job, operasi, mesin)
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ST = [[i + 1, 1, ROUTING[i][0]] for i in range(len(ROUTING))]
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# e. Melakukan pemrosesan pembuatan jadwal
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# Proses selesai dilaksanakan jika semua job selesai terjadwal
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print("Pemrosesan sedang dilakukan...")
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print("===== initial check ======")
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print("mesin ", MESIN)
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print("processing_time ", PROCESSING_TIME)
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print("routing ", ROUTING)
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print("CJ", CJ)
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print("TJ", TJ)
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print("RJ", RJ)
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print("ST", ST)
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print("----lesgo-----")
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while do_genetic_algo() != []:
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print("===== initial check ======")
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print("mesin ", MESIN)
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print("processing_time ", PROCESSING_TIME)
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print("routing ", ROUTING)
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print("CJ", CJ)
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print("TJ", TJ)
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print("RJ", RJ)
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print("ST", ST)
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print("----lesgo-----")
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pass
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# f. Semua job seledai dan hasil dicetak pada terminal
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print('\n---- Semua job telah selesai ----')
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print_schedule()
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input("\nPress Enter to Exit")

‎src/Non_delay.py‎

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for value in retval:
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i = ST.index(value)
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SCHEDULE.append([value[0], value[1], value[2], CJ[i], RJ[i]])
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if value[1] == 3:
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if value[1] == len(ROUTING[ST[i][0] - 1]):
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JOB_DONE.append([value[0], RJ[i]])
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# e. Lanjutan pemrosesan indexing untuk dikemas dalam senarai job dan machine

‎test3/Job1_Routing.txt‎

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1, 2, 3, 4

‎test3/Job1_Time.txt‎

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0.52, 1.08, 0.45, 0.1

‎test3/Job2_Routing.txt‎

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5, 2

‎test3/Job2_Time.txt‎

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0.1, 1.25

‎test3/Job3_Routing.txt‎

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6, 6, 7

‎test3/Job3_Time.txt‎

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2, 2, 0.75

‎test3/Job4_Routing.txt‎

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2

‎test3/Job4_Time.txt‎

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7.5

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