Pembangunan model pengoptimman pengeluaran minyak sawit dan isirong sawit menggunakan pendekatan genetik kabur

• Main Authors: ., Lily Amelia, Wahab, Dzuraidah, Hassan, Azmi
• Format: Article
• Language: English
• Published: Universiti Teknologi Malaysia 2008
• Subjects: QA76 Computer software; T55.4 Industrial engineering.Management engineering.
• Online Access: http://irep.iium.edu.my/37322/1/azmi3.pdf; http://irep.iium.edu.my/37322/; http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/220

Pengeluaran mirlyak sawit dan isirong sawit sering kali rnenghadapi masalah, antara lain kadar kehilangan minyak sawit dan isirong sawit yang tinggi semasa pemprosesan, dan penggunaan sumber-sumber yang tidak optimum. Model pengoptimuman pengeluaran minyak sawit dan isirong sawit perlu direka bentuk untuk menyelesaikan permasalahan tersebut sehingga dapat memaksimumkan hasil, meminimumkan kos pengeluaran serta meminimumkan kehilangan rninyak sawit dan isirong sawit. Model yang dibangunkan adalah gabungan antara model sistem pakar kabur dengan model pengaturcaraan pelbagai objektif. Pengoptimuman model dilakukan dengan menggunakan kaedah algoritma genetik. Model disimulasikan menggunakan data daripada sebuah kilang minyak sawit di Indonesia dan hasil kajian membuktikan pencapaian pengeluaran yang lebih baik serta kehilangan minyak sawit dan isirong sawit yang lebih kecil berbanding keadaan pengeluaran sedia ada di kilang minyak sawit tersebut. (The production of crude palm oil and palm kernel are frequented by problems, among others the high Ioss of crude palm oil and palm kernel during processing and the consumption of resources that are not optimised. An optimisation model for crude palm oil and palm kernel production has to be developed to solve these problems so as to maximise revenue, minimise production costs as well as to minimise palm oil and palm kernel losses. The developed model is an integration between fuzzy expert system models and multi objective programming model. Model optimisation is performed using the genetic algorithm method. The model was simulated using data from a palm oil mill in Indonesia and results from the study show that the model produces an optimum quantity of production and capable of reducing palm oil and palm kernel losses compared with the existing production conditions in the palm oil mill.)