Modeling of an Inventory System with Variable Demands and Lead Times using a Fuzzy Approach

Author(s):  
Vijay Kumar ◽  
Pravin Kumar

Inventory modeling has always been an innovative research topic for the researchers. It is concerned with minimization of the total inventory cost and maximization of the service level with minimum inventory. In the real world, the demand is always variable; and also the lead time of supply of an item cannot be always fixed due to some unavoidable circumstances. This chapter is focused on an inventory model with shortages where demand quantity and lead time are considered as variable and represented by triangular fuzzy numbers. An expression for optimum order size, reorder point, safety stock and fuzzy total safety stock cost is developed for a fixed customer service level. This model may help the manager to minimize the inventory cost with a maximum service level under the environment of uncertainty and vague information.

Author(s):  
Gerrit K. Janssens ◽  
Lotte Verdonck ◽  
Katrien Ramaekers

Facing uncertainty in demand, companies try to avoid stock-outs by holding safety inventories, depending on a pre-set customer service level. The knowledge of the demand distribution during lead-time serves to determine the safety inventory level. Many times the distribution is not fully known, except maybe for its range, mean or variance. However literature shows that the performance of holding safety stock strongly depends on the characteristics of the distribution. One option is to protect against the worst case distribution given some information like range or moments. But this worst case is a two-point distribution, bringing unbelief to managers that such an occurrence would ever appear. Mostly they share the opinion that the demand distribution is unimodal. This research develops a technique to derive the safety stock for unimodal demand distributions of which the mode either is known or can be estimated. In this way, the managers obtain solutions to the decision problem including a higher belief that the related type of distribution might appear in practice.


2014 ◽  
Vol 63 (8) ◽  
pp. 1046-1069 ◽  
Author(s):  
Sanjay Sharma ◽  
Akshat Sisodia

Purpose – The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model. Design/methodology/approach – Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations. Findings – After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time. Originality/value – Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.


Author(s):  
Abdul Rofiq ◽  
Oetari Oetari ◽  
Gunawan Pamudji Widodo

<p><strong>A</strong><strong>bstrak</strong><strong>: </strong>Pengelolaan persediaan obat yang optimal memberikan penghematan biaya pengadaan obat. Dua permasalahan sangat penting dalam pengendalian persediaan obat yaitu memutuskan jenis dan jumlah obat yang harus dipesan. Untuk mendapatkan solusi pengendalian persediaan maka diperlukan identifikasi dan analisis permasalahan tersebut. Tujuan penelitian ini menganalisis sistem pengendalian dan meningkatkan efisiensi siklus pengelolaan obat pasien BPJS Kesehatan klasifikasi AE di Instalasi Farmasi Rumah Sakit Bhayangkara Kediri. Obat klasifikasi AE menggambarkan obat dengan indek kritis tinggi dengan pemakaian dan <em>item</em> banyak, selanjutnya dianalisis menggunakan metode ABC, VEN dan EOQ. Jenis penelitian ini adalah penelitian deskriptif analitik, pengambilan data dilakukan secara retrospektif. Data yang digunakan obat pasien BPJS Kesehatan di Instalasi Farmasi Rumah Sakit Bhayangkara Kediri periode Januari - Desember 2018. Pengumpulan data primer dan sekunder melalui observasi dokumen di lapangan dan wawancara dengan pihak terkait. Analisis menggunakan metode ABC, VEN dan EOQ untuk klasifikasi obat AE. Selanjutnya hasil pengolahan data dibandingkan dengan parameter <em>Reorder Point</em>, <em>Inventory Value</em>, <em>Inventory Turn Over Ratio</em>, <em>Customer Service Level</em>, <em>Safety Stock</em> dan <em>Maximum level inventory</em> untuk menilai efisiensi pengendalian persediaan guna memperoleh persediaan obat yang efisien. Penelitian ini diperoleh hasil analisis pengendalian obat pasien BPJS Kesehatan menggunakan metode ABC dan VEN mampu meningkatkan pengelolaan obat menjadi efektif dan efisien khususnya obat katagori AE. Data perencanaan, pengadaan dan pemakaian obat pasien BPJS Kesehatan tahun 2018 dianalisis dengan metode EOQ selanjutnya dibandingkan nilai parameter yang digunakan dapat mengurangi nilai <em>Stock Out</em>, tetapi efektifitas dan efisiensi pengendalian obat tidak tercapai.</p>


2018 ◽  
Vol 7 (1) ◽  
pp. 41
Author(s):  
Carles Sitompul ◽  
Paulina Ariningsih ◽  
Ida Bagus Deva Narswara Santosa

<p><em>An inventory management system in supply chains called Vendor Managed Inventory (VMI) is very promising due to the cost efficiency resulted from implementing such system. This research aims to develop a vendor managed inventory for multiple retailers. The model also takes into account lead time uncertainties from vendor to its retailers. A mathematical formulation for VMI with multiple retailers is first developed using deterministic lead times.  Subsequently, lead times uncertainties are then taken into account where modes lead times are broken into two components: modes and delays, each with their respective probabilities. In turn, an approximation model is used to solve the problem because the complexity aroused from the model is difficult to solve using analytical methods. It is shown that the proposed approximation method is able to solve VMI problem with multiple retailers and uncertain lead times.  Furthermore, the total inventory cost is significantly reduced when compared to the usual economic order quantity method because stockouts are less frequent. </em></p>


2021 ◽  
Vol 9 (12) ◽  
pp. 650-660
Author(s):  
*Bolarinwa, Mojisola A. ◽  
Fajebe, Fisayo E.

Asides inventory cost, which is being used as the only inventory performance measure at the University of Ibadan bakery, a number of other criteria, such as inventory cost, service level, inventory turnover and delivery lead time which influence the performance of an inventory system have surfaced over the years. Hence, there is the need to examine all these criteria-objectives altogether. Therefore, this research was centred towards optimising the inventory system of University of Ibadan bakery, putting multiple criteria into consideration. Data on 17 raw materials: their costs, suppliers, usage rate, lead time, storage space and available capital were collected by means of interviews, past records and observations. The weighted goal program algorithm was adopted to find the best compromise between fulfilling the four objectives by minimising the sum of the deviation from the target values of the goals. Subsequently, Lingo 17.0 and Tora 1.0 optimisation software packages were used to solve and compare the model generated, while putting into consideration storage space constraint and budgeted capital. The developed model from the goal programming algorithm exhibited four goals (combined into one objective function). Same solutions were obtained from Lingo 17.0 and Tora 1.0. While Lingo 17.0 gave a  uniform service level of 100% , a  turnover ratio greater than 1(>1) for all the materials at a negligible increase (of  < 0.0001%) in total inventory cost of the raw materials and available lead time duration of zero days (< 24 hours) for each material, Tora 1.0  gave a  uniform service level of 100% , a  turnover ratio greater than 1 (> 1) for all the materials at a negligible increase (of  < 0.0001%) in total inventory cost of the raw materials and available lead time duration of zero days (< 24 hours) for each material. Implementation of the developed model will eliminate unnecessary waiting time between production, thereby ensuring effective and efficient utilisation of raw materials in production which will lead to reduced cost of holding inventory, elimination of unnecessary overall cost and wastages, and also improvement of the productivity and profit on the long run.


Kybernetes ◽  
2015 ◽  
Vol 44 (2) ◽  
pp. 176-185 ◽  
Author(s):  
Kazim Sari

Purpose – The purpose of this paper is to investigate the value of reducing errors in inventory information from a supply chain perspective. To this end, the benefits of reducing errors in inventory information are compared with those of lead time reduction and supply chain collaboration. Design/methodology/approach – A simulation model is constructed to perform the analysis. Findings – Results show that lead time reduction is the most important strategy for a supply chain in reducing total supply chain cost. In terms of customer service level, on the other hand, strategy of reducing errors in inventory information is observed as the most considerable strategy. However, the results for supply chain collaboration are somewhat unexpected. Namely, in spite of its popularity, supply chain collaboration provides very limited contribution to the supply chain. Practical implications – This research provides useful knowledge for the managers of a business enterprise in prioritizing various supply chain strategies. Originality/value – In supply chain management literature, greater emphasis is given to lead time reduction and supply chain collaboration than dealing with errors in inventory information. This research makes it clear that errors in inventory information should not be underestimated.


2011 ◽  
Vol 10 (01) ◽  
pp. 175-185 ◽  
Author(s):  
XIN JAMES HE ◽  
XIAOBO XU ◽  
JACK C. HAYYA

In a study on stochastic inventory systems, Chopra et al. (Decision Sciences35(1) (2004) 1–24) argue that decreasing lead time is the right lever if they want to cut inventories, not reducing lead time variability. According to Chopra et al., reducing the mean lead time, μ, is more important than reducing the lead time variance, σ2, to reduce total inventory cost via a reduced safety stock. This paper is a criticism of Chopra et al., where the optimal z was derived based upon a predetermined Q, instead of solving the optimal z and Q simultaneously in a (z, Q) inventory system. We argue that such an approach is inappropriate because the two decision variables, z and Q, are in general interdependent, and, moreover, reducing reorder point (safety stock), z, does not necessarily decrease the total inventory cost. We demonstrate by means of a truncated lead time (z, Q) model that it is lead time variability, not mean lead time, that affects the inventory policy and total supply chain cost.


Author(s):  
Monika Ahmelia ◽  
Herlin Herlin ◽  
Abdul Rahman

This study aims to analyze the stock inventory control of Mie Dzohir's raw materials in Bengkulu. The analytical method used is Economic Order Quantity (EOQ), Reorder Point (ROP), Total Inventory Cost (TIC) and Safety Stock (SS). The results showed that to meet the raw material needs of 91,375 kg during the research period, from January 2020 to December 2020 (12 months), the number of economical purchases/EOQ of wheat flour raw materials that had to be made by the Mie Dzohir factory in Bengkulu was as much as 5,372 kg for each order with a purchase frequency of 17 times for a period from January 2020 to December 2020. Reorders or reorder points (ROP) can also be determined, namely reordering should be done when 345 kg of inventory is in warehouse, with a lead time of 1 days so as not to hamper the company's production process. The total inventory cost (TIC) can also be determined, namely the total cost of raw material inventory of Rp. 3.572.188, - therefore, it can save on inventory costs of Rp. 1.051.697,- .Safety stock (SS) of 95 kg which must be in the warehouse, this is intended therefore, there is no shortage of wheat flour raw materials if there is a delay in the delivery of raw materials.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Ming-Feng Yang ◽  
Yi Lin ◽  
Li Hsing Ho ◽  
Wei Feng Kao

Nowadays, in order to achieve advantages in supply chain management, how to keep inventory in adequate level and how to enhance customer service level are two critical practices for decision makers. Generally, uncertain lead time and defective products have much to do with inventory and service level. Therefore, this study mainly aims at developing a multiechelon integrated just-in-time inventory model with uncertain lead time and imperfect quality to enhance the benefits of the logistics model. In addition, the Ant Colony Algorithm (ACA) is established to determine the optimal solutions. Moreover, based on our proposed model and analysis, the ACA is more efficient than Particle Swarm Optimization (PSO) and Lingo in SMEIJI model. An example is provided in this study to illustrate how production run and defective rate have an effect on system costs. Finally, the results of our research could provide some managerial insights which support decision makers in real-world operations.


2020 ◽  
Vol 6 (2) ◽  
pp. 94-99
Author(s):  
Niken Septiani Kurnia

Pengaplikasian model transhipment pada transportasi seringkali dijumpai dalam dunia bisnis, entah untuk konsolidasi ataupun membagi produk menjadi beberapa bagian sampai akhirnya dikirim ke tujuan. Kondisi seperti ini terkadang membuat perusahaan mengeluarkan biaya yang cukup besar untuk transportasi serta lead time produk sampai ke konsumen yang lebih panjang sehingga mempengaruhi customer service level, padahal sejatinya perusahaan menginginkan customer service level yang baik serta keuntungan yang maksimum dengan biaya yang minimum. PT. SBT yang merupakan perusahaan yang bergerak dalam bidang pendistribusian barang bangunan ini juga tidak terlepas dari kegiatan transportasi yang menerapkan sistem transhipment dengan kepemilikan 3 gudang sebagai tempat transit, dimana ketiga gudang ini memiliki lokasi yang berbeda-beda sehingga perlu dilakukan penelitian lebih lanjut apakah dengan adanya ketiga gudang tersebut biaya transportasi yang dikeluarkan sudah optimal atau belum. Penelitian dilakukan menggunakan data sekunder dari penelitian terdahulu dengan tujuan membandingkan hasil metode yang digunakan penelitian terdahulu dengan hasil penelitian ini, sehingga dapat memberikan masukan terbaik bagi perusahaan dalam aspek transportasi guna mencapai tujuan perusahaan. Pendekatan yang digunakan dalam menyelesaikan masalah transhipment ini yaitu menggunakan software Lingo yang tentunya dengan harapan memberikan hasil optimal. Hasil penelitian menunjukkan adanya penurunan total biaya transportasi yang awalnya Rp 3.275.000 menjadi Rp 1.413.000 dengan selisih biaya sebesar Rp 1.862.000 atau sebesar 56,85%.


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