OPTIMASI BIAYA TRANSPORTASI USAHA KELAUTAN : STUDI KASUS UDX KECAMATAN LABUHAN MARINGGAI

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Alfan Juli Andri ◽  
Keyword(s):  
Minimum Cost ◽  
Transportation Problems ◽  
Distribution Costs ◽  
Shipping Cost

Abstract As a maritime country, Indonesia is given an abundance of marine wealth. In an effort to distribute fish from sea products, fishermen in Labuhan Maringgai District, East Lampung Regency collect their prey to Usaha Dagang X (UDX). UDX has 3 main ordering partners for 3 categories of seafood, namely shrimp, fish and crab. Transportation problems at UDX cause distribution costs to increase in delivery of goods to the customer. This study provides an alternative minimum cost solution that can be issued by UDX in distributing goods that are available using existing limitations. The results showed that the minimum shipping cost was IDR 5281200 where the 3 proposed methods showed the same results but had different alternative options.

scholarly journals Absolute point algorithm for solving unbalanced fuzzy transportation problem

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
K. Rathi 1 ◽  
S. Muruganantham 2
Keyword(s):  
Real Time ◽  
Transportation Problem ◽  
Optimal Allocation ◽  
Minimum Cost ◽  
Market Demand ◽  
Absolute Point ◽  
Transportation Problems ◽  
Fuzzy Environment ◽  
Fuzzy Transportation Problem ◽  
Future Demands

 In real time situations, the total availability of goods or product may be more or less than the actual market demand and the unbalanced transportation situation arise more commonly. Such unbalanced Transportation Problems (TP) are solved by introducing dummy source or destination which do not exist in reality. The optimal allocation involves cells from such dummy source or destination and the allocated number of quantities are held back at one or more origins. The paper aims to propose an algorithm based on Absolute Points to solve unbalanced TP under fuzzy environment. The proposed algorithm is advantageous than the existing algorithms  in such a way that it provides the added information of transporting the excess availability from dummy supply point to appropriate destination to meet future demands at minimum cost. Finally, by virtue of the proposed algorithm an example is done to illustrate the practicality and the effectiveness of the proposed algorithm. 

scholarly journals The optimization of distribution and transportation costs for common good products

2020 ◽  
Vol 1 (2) ◽  
pp. 111
Author(s):  
Fibi Eko Putra ◽  
Humiras Hardi Purba ◽  
Indah Astri Anggraeni
Keyword(s):  
Cost Reduction ◽  
Common Good ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Distribution Model ◽  
Transportation Problems ◽  
Stepping Stone ◽  
North West ◽  
Long Time ◽  
Single Method

Transportation problems, which concerned in finding the minimum cost of transporting a single commodity from a given number of sources to a given number of destinations, are an integral part of the industrial system that has been around for a long time. The number of potential losses caused by transportation problems has made many parties take initiatives and efforts to solve those problems, usually by designing an optimal distribution model. The current study employs two methods named North West Corner (NWC) and Stepping Stone (SS) method in order to find distribution model with the most optimal costs for common good products. Through this research, the NWC method is utilized to generate initial model or solution, while the SS method is used afterward to find the optimal solution. According to it scheme, the result shows that through the NWC method there was cost reduction of $ 8,301, while the distribution model obtained from the Stepping Stone method resulted in a significant cost increased of $ 307,369. Thus, it can be concluded that the use of single method, namely NWC method, in this study provides much better results than using the combined NWC and Stepping Stone method.

scholarly journals Optimization Model of Marketing Distribution Fish Processed Products by Transportation Method

2020 ◽  
Vol 008 (01) ◽  
pp. 68-81
Author(s):  
Harsuko Riniwati ◽  
◽  
Lina Asmara Wati ◽  
Eko Waluyo ◽  
Mentari Puspa Wardani ◽  
...  
Keyword(s):  
Optimization Model ◽  
Minimum Cost ◽  
Optimization Method ◽  
Linear Program ◽  
Transportation Problems ◽  
Maximum Profit ◽  
Processed Products ◽  
Marketing Costs ◽  
Method Model ◽  
Processing Group

The transportation model is a variation of a linear program developed specifically to problems solve related to transportation and the distribution of products from various sources to various destinations. The goal of transportation problems is to allocate goods at the source that all needs are met at the destination of the demand location. The purpose of this study is to analyze the allocation of the delivery of processed catfish products in POKLAHSAR Kediri Regency from the processing location to the market destination with the minimum allocation of marketing costs. The data were obtained from the catfish product processing group in Kediri Regency. Data were analyzed using the transportation optimization method model. The results of the analysis show that all factory capacities can meet the demands of all markets. There is not a single market that is not fulfilled. Suggestions for the research that the maximum profit can be achieved is the allocation of factory 1 product shipments to Tulungagung 165 packs and Ponorogo 65 packs. Factory 2 sent 220 packs to Ponorogo, Surabaya 50 packs, Jakarta 130 packs. Factory 3 sent to Tulungagung 50 packs. Factory 4 sends 100 packs to Ponorogo with a total minimum cost of IDR 620,000.

scholarly journals Kajian Tentang Metode Zero Suffix Menggunakan Teknik Robust Ranking Pada Masalah Transportasi Dengan Variabel Fuzzy

2018 ◽  
Vol 1 (1) ◽  
pp. 016-023
Author(s):  
Siti Ramadhani ◽  
Ujian Sinulingga ◽  
Esther Nababan
Keyword(s):  
Everyday Life ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Minimum Cost ◽  
Transportation Costs ◽  
Transportation Problems ◽  
Fuzzy Variables ◽  
Ranking Technique ◽  
Reduction Of Costs

Permasalahan transportasi merupakan permasalahan yang sering terjadi dalam kehidupan sehari-hari. Masalah transportasi dengan jumlah supply, jumlah demand, dan biaya angkutannya dinyatakan dengan bilangan fuzzy disebut sebagai masalah transportasi fuzzy. Dalam menyelesaikan masalah transportasi fuzzy, tabel fuzzy harus diubah terlebih dahulu ke bentuk linier agar lebih mudah dalam mengerjakannya.Teknik Robust Ranking merupakan suatu teknik yang digunakan untuk mengubah masalah transportasi fuzzy menjadi permasalahan transportasi linier. Untuk mencari solusi yang optimal metode yang digunakan untuk menyelesaikan masalah transportasi dengan variabel fuzzy adalah metode Zero Suffix. Metode Zero Suffix dimulai dengan pengurangan biaya di dalam tablo baris dengan biaya yang paling minimum pada baris, kemudian dilanjutkan pengurangan biaya di dalam tablo kolom dengan biaya paling minimum pada kolom. Selanjutnya mencari suffix value dari masing-masing kolom, dengan memilih suffix value terbesar. Dilanjutkan memilih biaya nol pada tablo transportasi lalu memilih minimum dari permintaan dan persediaan dilanjutkan mengalokasikannya ke dalam tablo. Pencarian suffix value ini tetap berlanjut sampai semua baris dan kolom sudah jenuh. Transportation problems are issues that often occur in everyday life. The problem of transportation with the amount of supply, number of demand, and transportation costs expressed by fuzzy numbers is referred to fuzzy transportation problems. In solving fuzzy transportation problems, fuzzy tables must be changed first to linear shapes so that they are easier to do. Robust ranking technique is a technique used to convert fuzzy transportation problems into linear transportation problems. To find the optimal solution, the Zero Suffix method was used to solve transportation problems with fuzzy variables. The Zero Suffix method started with the reduction of costs in the table row with the minimum cost in the row, then continued to reduce costs in the table column with the minimum cost in the column. Subsequently, it looked for the suffix value of each column, by selecting the largest suffix value. It proceeded to choose zero costs for the transportation tableau, chose the minimum of the demand and the inventory, and then continued to allocate it to the tableau. Searching for the suffix value continued until all rows and columns were saturated. 

Maximum production — minimum cost via value analysis

1963 ◽  
Vol 42 (3) ◽  
pp. 147
Author(s):  
N. Taylor
Keyword(s):  
Minimum Cost ◽  
Value Analysis ◽  
Maximum Production

A generalized fuzzy cost efficiency model

2020 ◽  
Vol 54 (6) ◽  
pp. 1775-1791
Author(s):  
Nazila Aghayi ◽  
Samira Salehpour
Keyword(s):  
Cost Efficiency ◽  
Minimum Cost ◽  
Extensive Literature ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Decision Making Unit ◽  
Production Possibility Set ◽  
Fuzzy Cost ◽  
The Cost ◽  
Generalized Cost

The concept of cost efficiency has become tremendously popular in data envelopment analysis (DEA) as it serves to assess a decision-making unit (DMU) in terms of producing minimum-cost outputs. A large variety of precise and imprecise models have been put forward to measure cost efficiency for the DMUs which have a role in constructing the production possibility set; yet, there’s not an extensive literature on the cost efficiency (CE) measurement for sample DMUs (SDMUs). In an effort to remedy the shortcomings of current models, herein is introduced a generalized cost efficiency model that is capable of operating in a fuzzy environment-involving different types of fuzzy numbers-while preserving the Farrell’s decomposition of cost efficiency. Moreover, to the best of our knowledge, the present paper is the first to measure cost efficiency by using vectors. Ultimately, a useful example is provided to confirm the applicability of the proposed methods.

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