Mencari biaya minimum pengirim barang suatu perusahaan masih merupakan hal penting yang perlu dikaji agar dapat menekan biaya pengeluaran perusahaan. Oleh karena itu, banyak penelitian yang terus dilakukan untuk mencari biaya minimum (solusi optimal) masalah transportasi. Artikel ini bertujuan untuk mencari biaya minimum masalah transportasi yang diharapkan dapat mengoreksi penelitianpenelitian sebelumnya. Penulis menggunakan metode baru yaitu metode Sirisha-Viola. Berdasarkan perhitungan yang telah dilakukan diperoleh nilai optimal dari biaya transportasi pada studi kasus diperoleh sebesar Rp. 1.335.000,-. Oleh karena itu biaya terkecil masalah transportasi adalah sebesar Rp. 1.335.000,-.

This paper discusses the optimal solution for specific types of optimization problems called fuzzy transportation problems using pentagonal fuzzy numbers. Cost value, supply, and the demand for fuzzy transport issues are taken as fuzzy numbers pentagonal. Pentagonal fuzzy numbers are converted to crisp values using functions recommended for new rankings. The purpose of this study is to compare new ranking methods with old rankings as well as Vogel's Approximation Method (VAM) and Max Min Voge'l Approximation Method (MM-VAM) in finding optimal solutions to fuzzy transportation problems. From the results of the study, it was obtained that the new ranking method with VAM method gets the smallest transportation cost. Press Proceedings article template has many predefined paragraph styles for you to use/apply as you write your paper.

One of the problems that exist in operations research is the problem of transportation. This study proposes the completion of the optimal solution in the transportation problem using the Modified Method of the Sirisha Viola method. The method proposed hereinafter is called the Sirisha Viola Modified Method . The algorithm in this method is the same as in the Sirisha Viola method but differs in the allocation step, where the allocation is made to the minimum demand first, then compared with the corresponding supply value. The data used in this study consisted of secondary data and simulated data (random data). The results of numerical calculations or using the help of the Python program for secondary data obtained an optimal solution of 12,100 cost units. Whereas for random data consisting of 4 0 balanced data and 40 unbalanced data with sizes 10 x 10, 13 x 17, 25 x 27, and 50 x 50 the optimal solution results are obtained. It is concluded that the Sirisha Viol a Modification Method in solving transportation problems can produce optimal solutions directly without the need to determine the initial feasible solution.