Implementasi Algoritma Hybrid Cross Entropy–Genetic Algorithm Untuk Menyelesaikan Single Stage Capacitated Warehouse Location Problem (Studi Kasus: PT Petrokimia Gresik)

Lahdji, Fatmah Munif (2016) Implementasi Algoritma Hybrid Cross Entropy–Genetic Algorithm Untuk Menyelesaikan Single Stage Capacitated Warehouse Location Problem (Studi Kasus: PT Petrokimia Gresik). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Single stage capacitated warehouse location problem (SSCWLP)
merupakan permasalahan alokasi distribusi dimana produk akan dikirimkan dari
plant menuju warehouse untuk selanjutnya dikirimkan dari warehouse menuju
pelanggan. Permasalahan SSCWLP ini merupakan permasalahan NP-hard dimana
penyelesaiannya menggunakan metode eksak membutuhkan waktu yang lama
sehingga sering didekati dengan metode metaheuristik. Penelitian ini berfokus
pada penentuan alokasi distribusi pupuk PT. Petrokimia Gresik di Pulau
Sumatera. Penentuan alokasi distribusi pupuk dilakukan menggunakan algoritma
hybrid cross entropy – genetic algorithm. Algoritma ini menggabungkan antara
mekanisme pembangkitan sampel pada cross entropy dengan mekanisme mutasi
pada genetic algorithm sebagai upaya untuk mempercepat waktu komputasi
algoritma cross entropy original. Hasil komputasi menggunakan algoritma hybrid
cross entropy genetic algorithm menunjukkan penghematan biaya distribusi
sebesar Rp 737.780.842,00 dengan membuka empat gudang lini 3, antara lain GP
Solok, GP Bukittinggi, GP Merangin, dan GP Kotabumi. Berdasarkan hasil
eksperimen yang dilakukan, diketahui bahwa secara umum algoritma hybrid cross
entropy – genetic algorithm mampu menghasilkan alternatif solusi yang lebih
mendekati optimum dibandingkan algoritma metaheuristik lain seperti algoritma
simulated annealing. Selain itu, algoritma hybrid cross entropy – genetic
algorithm juga menghasilkan solusi yang lebih mendekati optimum dengan waktu
komputasi yang lebih cepat dibangingkan algoritma cross entropy original, dan
genetic algorithm tanpa crossover.

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Single stage capacitated warehouse location problem (SSCWLP) is an
allocation problem in which products will be distributed from the plant to the
warehouse for further distributed from the warehouse to the customer. SSCWLP
is NP-hard problem, where finding the solution using exact method requires a
longer computational time, thus this problem often solved with metaheuristics
approach. This study focuses on determining allocation of fertilizer distribution in
PT Petrokimia Gresik on Sumatera Island. This allocation problem is computed
using a hybrid cross entropy – genetic algorithm method. This algorithm
combines the mechanisms of generating samples on cross entropy with mutations
mechanism on genetic algorithm in order to speed up the computational time of
original cross entropy algorithm. The computational result shows distribution cost
savings up to Rp 737.780.842,00 by opening only four gudang lini 3, which are
GP Solok, GP Bukittinggi, GP Merangin, and GP Kotabumi.Based on the
experimental results, it is known that in general, hybrid cross entropy - genetic
algorithm is capable of generating an alternative solution which is closer to the
optimum compared to other metaheuristic algorithms such as simulated annealing
algorithm. In addition, the hybrid cross entropy algorithm - genetic algorithm also
generates solution that is both closer to the optimum solution and has faster
computational time compared to original cross entropy algorithms and genetic
algorithm without crossover.

Item Type: Thesis (Undergraduate)
Additional Information: RSI 658.5 Lah i
Uncontrolled Keywords: Cross Entropy-Genetic Algorithm; Metaheuristik; Single Stage Capacitated Warehouse Location Problem
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.546 Computer algorithms
Divisions: Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis
Depositing User: Anis Wulandari
Date Deposited: 15 Jun 2017 04:32
Last Modified: 27 Dec 2018 02:21
URI: http://repository.its.ac.id/id/eprint/41690

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