Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up

Dana Marsetiya Utama, Teguh Baroto, Dewi Maharani, Fathiha Raudhatul Jannah, Ricca Andhini Octaria

Abstract


Industri manufaktur akhir-akhir ini dituntut untuk memperhatikan isu lingkungan. Pemakaian energi pada produksi umumnya menghasilkan emisi karbon. Emisi karbon ini menjadi permasalahan di lingkungan. Untuk mengurangi pemakaian emisi karbon, penelitian ini menggabungkan metode penjadwalan dan emisi karbon sebagai solusi dalam masalah lingkungan. Kasus pada artikel ini adalah flow shop dependent sequence set-up. Jurnal ini mengusulkan algoritma baru Ant Lion Optimizer (ALO) yang terinspirasi oleh alam untuk meminimasi emisi karbon. Beberapa percobaan numerik dilakukan untuk mengetahui parameter terbaik dari Algoritma ALO. Untuk menguji keefektifan dari algoritma, Algoritma ALO ini dibandingkan dengan beberapa algoritma populer saat ini. Hasil percobaan numerik menunjukan algoritma ALO efektif untuk meminimasi emisi karbon.

ABSTRACT

Manufacture industry recently is required to pay attention of enviromental issue. The use of energy in production generally produces carbon emissions. This carbon emission is a problem in the environment. This study combines scheduling methods and carbon emissions as a solution to environmental issues to reduce the use of carbon emissions. The case in this article is the flow shop dependent sequence set-up. This journal proposes a new Ant Lion Optimizer (ALO) algorithm inspired by nature to minimize carbon emissions. Several numerical experiments were conducted to determine the best parameters of the ALO algorithm. This ALO algorithm is compared with several popular algorithms today. The numerical experiment results show that the ALO algorithm is useful for minimizing carbon emissions.


Keywords


ant lion optimization; penjadwalan; flow shop; dependent sequence setup; emisi karbon

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DOI: http://dx.doi.org/10.24960/jli.v9i1.4775.69-78

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