scholarly journals Fuzzy economic order quantity model with ranking fuzzy number cost parameters

2012 ◽  
Vol 22 (2) ◽  
pp. 247-264 ◽  
Author(s):  
Nirmal Mandal
Keyword(s):  
Fuzzy Numbers ◽  
Unit Cost ◽  
Real Life ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Programming Approach ◽  
Order Quantity ◽  
Inventory Problem ◽  
Numerical Illustration ◽  
Cost Parameters

In this paper, a multi-objective economic order quantity model with shortages and demand dependent unit cost under storage space constraint is formulated. In real life situation, the objective and constraint goals and cost parameters are not precisely defined. These are defined in fuzzy environment. The cost parameters are represented here as triangular shaped fuzzy numbers with different types of left and right branch membership functions. The fuzzy numbers are then expressed as ranking fuzzy numbers with best approximation interval. Geometric programming approach is applied to derive the optimal decisions in closed form. The inventory problem without shortages is discussed as a special case of the original problem. A numerical illustration is given to support the problem.

scholarly journals Pengendalian Persediaan Bahan Baku Nalco Water Treatment Dengan Menggunakan Metode Lot Sizing

2019 ◽  
Vol 2 (2) ◽  
pp. 80
Author(s):  
Masad Hariyadi ◽  
Boy Isma Putra
Keyword(s):  
Water Treatment ◽  
Raw Materials ◽  
Unit Cost ◽  
Exponential Smoothing ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Double Exponential ◽  
Double Exponential Smoothing

The limited supply of Nalco raw materials from producers has become a problem for PT ABC, this has led to the control of raw material inventory at PT ABC not including good management, because in the management of raw materials the company still records inventory with manual systems and in ordering raw materials only based on estimates. From the results of the study, the forecasting method used is the Double Exponential Smoothing Holt's, Brown, and Holt Winters Additive Algorithm methods, from the three methods that are most suitable is the Double Exponential Smoothing Brown method with the smallest Mean Square Error of 256.2. Calculation of Sizing Lot by using Economic Order Quantity method, Least Unit Cost method, and Silver Meal method, of the three methods the most optimal is the Economic Order Quantity method because it has the lowest cost of Rp. 12,651,145. The calculation of Safety Stock gets 17 Pail results. and for Reorder Points for Nalco Water Treatment raw material, which is 29 Pail.

scholarly journals The Economic Order Quantity in a Fuzzy Environment for a Periodic Inventory Model with Variable Demand

2022 ◽  
pp. 102-107
Author(s):  
K. Kalaiarasi ◽  
MARY HENRIETTA H ◽  
M. Sumathi ◽  
A. Stanley Raj
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Analysis ◽  
Fuzzy Numbers ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Critical Part ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment

The technique of limiting expenditure plays a critical part in an organization's ability to govern the smooth operation of its management system. The economic order quantity (EOQ) is calculated by solving a nonlinear problem, and the best solution is investigated in a fuzzy and intuitionistic fuzzy environment. The overall cost is made up of several factors, such as demand, holding, and ordering costs. The demand and stock-out characteristics were both fuzzified using fuzzy and intuitionistic fuzzy numbers. The numerical analysis shows the comparison between the two fuzzy numbers through sensitivity analysis.

scholarly journals The Fuzzy Economic Order Quantity Problem with a Finite Production Rate and Backorders

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Kaj-Mikael Björk
Keyword(s):  
Fuzzy Numbers ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Economic Production Quantity ◽  
Eoq Models ◽  
Economic Production ◽  
Epq Model ◽  
Production Quantity ◽  
Industrial Context

The track of developing Economic Order Quantity (EOQ) models with uncertainties described as fuzzy numbers has been very lucrative. In this paper, a fuzzy Economic Production Quantity (EPQ) model is developed to address a specific problem in a theoretical setting. Not only is the production time finite, but also backorders are allowed. The uncertainties, in the industrial context, come from the fact that the production availability is uncertain as well as the demand. These uncertainties will be handled with fuzzy numbers and the analytical solution to the optimization problem will be obtained. A theoretical example from the process industry is also given to illustrate the new model.

scholarly journals Determination of Economic Order Quantity in a fuzzy EOQ Model using of GMIR Deffuzification

2017 ◽  
Vol 2 (1) ◽  
pp. 76 ◽  
Author(s):  
Hamidreza Salmani Mojaveri ◽  
Vahid Moghimi
Keyword(s):  
Inventory Control ◽  
Fuzzy Numbers ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Control Policies ◽  
Eoq Model ◽  
Cost System ◽  
The Cost

Inappropriate inventory control policies and its incorrect implementation can cause improper operation and uncompetitive advantage of organization logistic operation in the market. Therefore, analysis inventory control policies are important to be understood, including carrying cost, ordering cost, warehouse renting cost, and buying cost. In this research, Economic Order Quantity (EOQ) problem in fuzzy condition is reviewed in two different situations. The first model concerned to costs (carrying cost, ordering cost, warehouse renting cost and buying cost), which is considered as triangular fuzzy numbers. The second model was in addition to inventory the cost system, in which annual demand is also reviewed as fuzzy numbers. In each model, graded mean integration representation (GMIR) deffuzification was used for parameters deffuzification. Then, the final objective from this analysis was to obtain economic quantity formula through derivation.

ANALISA SISTEM PERSEDIAAN BAHAN BAKU PADA INDUSTRI BINTANG PRIMA ACEH BESAR

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Chairul Amni
Keyword(s):  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity

Perencanaan persediaan bahan baku merupakan salah satu peranan yang sangat penting dalam dunia industri untuk meningkatkan permintaan pasar. Sebuah perencanaan produksi akan berjalan dengan baik jika di dukung dengan adanya persediaan bahan baku yang memadai. Persediaan bahan baku juga memberikan kontribusi biaya yang cukup besar sehingga komponen biaya ini juga perlu untuk dikendalikan. Melihat pentingnya fungsi perencanaan produksi dan pengendalian persediaan bahan baku, maka perlu adanya usaha untuk mengelolanya secara efisien untuk mendapatkan hasil yang optimal. Perencanaan bahan baku merupakan hal yang sangat penting dilakukan untuk mendukung proses produksi, sehingga tidak terjadi masalah seperti keterlambatan pengiriman barang kepada konsumen, dan pemborosan biaya bahan baku. Tujuan dari penelitian ini adalah untuk mengetahui sistem pengendalian bahan baku yang diterapkan serta untuk mengetahui jumlah ekonomis bahan baku pada setiap kali pemesanan yang di analisis dengan menggunakan metode EOQ (Economic Order Quantity). Dari penelitian ini mendapatkan hasil yang menunjukkan bahwa penggunaan metode EOQ dalam pemesanan bahan baku jauh lebih optimal dan efisien dibanding metode yang selama ini diterapkan, terlihat dari selisih total biaya pemesanan bahan baku pada tepung mencapai 1,21% (404.950 rupiah) selisih pada bahan baku gula 0,02% (4.450 rupiah) dan selisih biaya pada pemesanan ragi dan garam sebesar 14,31% yaitu sebesar Rp. 82.500 untuk Ragi dan Rp. 8.250 untuk selisih pemesanan garam. dengan demikian dapat disimpulkan bahwa penggunaan metode EOQ mempuanyai hasil baik dalam melakukan pemesanan bahan baku sehingga bahan baku untuk produksi tidak mengalami penumpukan dan tidak mengalami kekosongan dalam gudang.

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