PENGEMBANGAN INCESSANT ALLOCATION METHOD – PRIORITY VALUE UNTUK MENCARI INITIAL BASIC FEASIBLE SOLUTION PADA TRANSPORTATION PROBLEM

Muswar, Aisyah (2020) PENGEMBANGAN INCESSANT ALLOCATION METHOD – PRIORITY VALUE UNTUK MENCARI INITIAL BASIC FEASIBLE SOLUTION PADA TRANSPORTATION PROBLEM. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Hampir setiap tahun, perusahaan manufaktur mengeluarkan biaya jutaan dolar untuk pendistribusian barang. Kemajuan perusahaan pun berbanding lurus dengan efisiensi metode transportasi perusahaan. Permasalahan ini mendorong para peneliti untuk melakukan riset dalam mencari biaya minimal, yang kemudian dikenal sebagai Transportation Problem (TP). TP merupakan bagian dari Linier Programming, baik pada bidang aplikasi matematika maupun riset operasional. Ada dua proses untuk mencari solusi optimal dari TP. Pertama adalah mencari Initial Basic Feasible Solution (IBFS) dan kedua adalah mencari solusi optimal dari IBFS menggunakan stepping stone. IBFS merupakan solusi awal dengan menggunakan algoritma tertentu sedemikian rupa sehingga biaya pengiriman pada TP mendekati angka paling minimal. Berbagai riset telah dilakukan oleh peneliti untuk mencari algoritma IBFS, salah satunya adalah Incessant Allocation Method - Priority Value (IAM-PV). IAM-PV merupakan algoritma IBFS yang menggunakan metode pengalokasian terus menerus pada tiap rute dengan memperhatikan nilai prioritas terbesar dari perbandingan hitungan row priority value dan column priority value, hingga semua rute terisi. Pada penelitian ini, algoritma IAM-PV akan dimodifikasi pada bagian inisiasi matriks awal. Modifikasi ini dinamakan Total Opportunity Cost Matrix – Priority Value (TOCM-PV). Algoritma tersebut diimplementasikan dalam bentuk program berbahasa C dengan format input sejumlah supply, sejumlah demand, dan cost tiap rute. Output yang diharapkan dari program ini adalah nilai alokasi tiap rute dan total biaya pengalokasian tersebut. Algoritma IAM-PV dan TOCM-PV diujicobakan terhadap 85 data. Pada hasil uji penelitian ini, persentase akurasi algoritma IAM-PV sebesar 16,47%, sedangkan persentase akurasi algoritma TOCM-PV sebesar 18,82%. Selain itu, TOCM-PV lebih baik daripada IAM-PV, hal ini dibuktikan dengan 44 data dari 85 data uji coba dapat mencapai hasil biaya lebih rendah dari IAM-PV. Sehingga pada penelitian ini dapat disimpulkan bahwa algoritma TOCM-PV lebih mendekati hasil optimal daripada algoritma IAM-PV. ============================================================================================== Almost every year, manufacturing companies issues millions of dollars in the distribution of goods. The company's progress is directly proportional to the efficiency of the company's transportation methods. This problem encouraged researchers to conduct research in looking for minimal costs, which became known as the Transportation Problem (TP). TP is part of Linear Programming, both in the field of mathematical applications and operational research. There are two processes to find the optimal solution from TP. First is looking for Initial Basic Feasible Solution (IBFS) and second is looking for optimal solutions from IBFS using stepping stones. IBFS is an initial solution that is provided using certain algorithms in such a way that shipping costs on TP approach the minimum amount. Various studies have been conducted by researchers to look for the IBFS algorithm, one of which is the Incessant Allocation Method - Priority Value (IAM-PV). IAM-PV is an IBFS algorithm that uses a continuous allocation method on each route by taking into account the greatest priority value from the ratio of row priority value and column priority value, until all routes are filled. In this study, the IAM-PV algorithm will be modified in the initial matrix initiation section. Modification of this method is called the Total Opportunity Cost Matrix - Priority Value (TOCM-PV). The algorithm is implemented in the form of a C-language program with the input format of a number of supplies, a number of demands, and the cost of each route. The expected output from this program is the value of the allocation of each route and the total allocation costs. IAM-PV and TOCM-PV algorithms were tested on 85 data. In the test results of this study, the percentage accuracy of the IAM-PV algorithm was 16.47%, while the percentage accuracy of the TOCM-PV algorithm was 18.82%. In addition, TOCM-PV is better than IAM-PV is better than IAM-PV, this is proven by 44 data from 85 trial data that can achieve lower cost results than IAM-PV. So in this study it can be concluded that the TOCM-PV algorithm is closer to optimal results than the IAM-PV algorithm.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: distribusi produk, biaya minimal, transportation problem, total opportunity cost matrix priority value , algoritma incesant allocation method priority value, product distribution, minimal costs, transportation problems, total opportunity cost matrix priority value, accession allocation method priority value algorithm
Subjects: Q Science > QA Mathematics > QA76.6 Computer programming.
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.546 Computer algorithms
Divisions: Faculty of Information and Communication Technology > Informatics > 55201-(S1) Undergraduate Thesis
Depositing User: Aisyah Muswar
Date Deposited: 12 Aug 2020 05:43
Last Modified: 12 Aug 2020 05:43
URI: https://repository.its.ac.id/id/eprint/77375

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