Comparative Analysis of Colliding Bodies Optimization-based Inventory Management over other Heuristics: Cloud with Blockchain Criteria

Author(s):  
C Govindasamy ◽  
A. Antonidoss
PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247144
Author(s):  
Khurram Rehmani ◽  
Afshan Naseem ◽  
Yasir Ahmad ◽  
Muhammad Zeeshan Mirza ◽  
Tasweer Hussain Syed

Inherent uncertainties in demand and supply make it problematic for supply chains to accomplish optimum inventory replenishment, resulting in loss of sales or keeping excessive inventories. To cope with erratic demands, organizations have to maintain excessive inventory levels, sometimes taking up to one-third of an organization’s annual budget. The two most pressing concerns to handle in inventory management are: how much to order and when to order. Therefore, an organization ought to make the correct and timely decisions based on precise demand information to avoid excessive inventory accumulation resulting in enhanced competitive advantage. Owing to the significance of inventory control and analysis, this paper reports on developing and successfully implementing a hybrid framework for optimum level inventory forecasting in Technical Services Organizations. The proposed framework is based on a case study of one of Pakistan’s leading Technical Services Organization. The paper presents a statistical analysis of historical data and a comprehensive fault trend analysis. Both these analyses set a solid foundation for the formulation of a comparative analysis matrix based upon price and quantity based analysis of inventory. Finally, a decision criterion (Forecasting Model) is proposed using three primary forecasting techniques with minimum error calculations. The study’s finding shows a forecast error of 142.5 million rupees in the last five years, resulting in the accumulation of more than 25 thousand excessive inventory stock. Application of price and quantity based analysis identifies that 65% of the annual budget is significantly dependent upon only 9% (in terms of quantity) of "High Price and Small Quantity" Items (HS). These HS items are forecasted through three different forecasting methods, i.e., Weighted Moving Average, Exponential Smoothing, and Trend Projection, with Minimum Absolute Deviation to significantly reduce the forecasting error while predicting the future required quantity. The research work aims to contribute to the inventory management literature in three ways. First, a new comparative analysis matrix concept for identifying the most critical items is introduced. Second, a Multi-Criteria Forecasting Model is developed to capture a wide range of operations. Third, the paper suggests how these forecasting criteria can be integrated into a single interactive DSS to maintain optimum inventory level stock. Even though the DSS framework is based on data from a single organization, the application is expected to manage inventory stock in a wide range of manufacturing and services industries. This study’s proposed hybrid framework is the first of its kind that encapsulates all four dimensions of inventory classification criteria, forming a multi-criteria hybrid model within a DSS framework.


2021 ◽  
pp. 106-113
Author(s):  
В.А. Полуэктов ◽  
Е.М. Якутин

Введение. Статья является продолжением исследования авторов, посвященного сравнению наиболее известных и распространенных методов управления запасами. В настоящей статье представлены результаты расчетов числового примера по ряду алгоритмов, приведен сравнительный анализ полученных данных, сформулированы рекомендации по использованию рассмотренных методов на практике, при условии соответствия допущениям, заложенным в приведенных расчетах. Данные и методы. В статье проведены расчеты общих затрат на поддержание запасов такими методами, как алгоритм Вагнера-Уайтина (Wagner-Whiting algorithm), эвристический метод Гроффа (Groff`s Rule), метод баланса затрат (Part Period Balancing, PPB), метод периодического размера заказа (Periodic Ordering Quantity, POQ). Результаты указанных расчетов объединены с полученными ранее в предыдущей публикации по данной проблематике. Сравнение полученных результатов позволило выделить на основе ранжирования наиболее оптимальные методы управления запасами в условиях сделанных допущений. Полученные результаты. Авторами сформулированы выводы относительно применения рассмотренных методов управления запасами на практике. Исходя из соотнесения отдельных элементов общих затрат на поддержание запасов даны соответствующие рекомендации. Выделены проблемы при определении размеров оптимальных партий пополнения запасов в случаях, когда на практике реальные условия (переменные модели) будут существенно отличаться от условий рассмотренного числового примера. Заключение. Результаты представленной публикации могут быть использованы на практике хозяйствующими субъектами, деятельность которых связана с созданием и поддержанием значительных объемов запасов, в целях оптимизации партий их поставок по критерию минимума общих затрат на хранение и пополнение Introduction. The article is a continuation of the authors ' research on the comparison of the most well-known and common methods of inventory management. This article presents the results of numerical calculations of example, a number of algorithms, a comparative analysis of the data obtained, recommendations for using the methods in practice, provided that the assumptions used in the calculations. Data and methods. The article calculates the total cost of maintaining inventory using such methods as the Wagner-Whiting algorithm, the Groff's Rule heuristic method, the Part Period Balancing (PPB) method, and the Periodic Ordering Quantity (POQ) method. The results of these calculations are combined with those obtained earlier in the previous publication on this issue. A comparison of the results obtained allowed us to identify, on the basis of ranking, the most optimal methods of inventory management, under the conditions of the assumptions made. The received results. The authors draw conclusions about the application of the considered methods of inventory management in practice. Based on the correlation of individual elements of the total cost of maintaining stocks, appropriate recommendations are given. Problems are identified in determining the size of optimal replenishment batches in cases where in practice the real conditions (model variables) will differ significantly from the conditions of the considered numerical example. Conclusion. The results of the presented publication can be used in practice by economic entities whose activities are associated with the creation and maintenance of significant volumes of stocks, in order to optimize the batches of their supplies according to the criterion of the minimum total cost of storage and replenishment.


2019 ◽  
Vol 3 (1) ◽  
pp. 14-22
Author(s):  
Sudarmawan Samidi

In countries with government-owned railways, the subsidies required to maintain service were becoming a serious burden on the state. Declining revenues have left the rail industry struggling to overcome operating deficits and to reduce subsidies from governments. This study aims to analyze the financial performance of Indonesia and Taiwan urban rail system. Financial ratios are employed to measure the profitability, liquidity, activity, and solvency performance of PT. Kereta Api Indonesia (KAI) and Taiwan High Speed Rail (THSR). The data were collected from both companies in the period of 2011-2015 based on its audited inancial report. In addition, the Decree No. KEP-100/MBU/2002 issued by Indonesia Ministry of SOEs was used to validate the inancial health condition with the level of financial assessment. The result showed that KAI had better financial performance in comparison with THSR. Generally, both companies have a challenge in asset utilization and inventory management. Therefore, this study is useful for the managers to tackle the challenges and improve its eficiency. Furthermore, this study could be policy options might be taken to improve both urban railways' performance.


2007 ◽  
Vol 177 (4S) ◽  
pp. 398-398
Author(s):  
Luis H. Braga ◽  
Joao L. Pippi Salle ◽  
Sumit Dave ◽  
Sean Skeldon ◽  
Armando J. Lorenzo ◽  
...  
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