Forecasting Methods and Optimization Models for the Inventory Management of Perishable Products: The Case of “La Centrale del Latte di Vicenza SpA”

2019 ◽  
pp. 87-98
Author(s):  
Luca Bertazzi ◽  
Francesca Maggioni
Keyword(s):  
Inventory Management ◽  
Optimization Models ◽  
Perishable Products ◽  
Forecasting Methods

Data Mining for Combining Forecasts in Inventory Management

2008 ◽  
pp. 2792-2797
Author(s):  
Chi Kin Chan
Keyword(s):  
Data Mining ◽  
Inventory Management ◽  
Traditional Approach ◽  
The Past ◽  
Aggregate Information ◽  
Forecasting Methods ◽  
Combining Forecasts ◽  
Forecasting Method ◽  
The Future ◽  
Single Method

The traditional approach to forecasting involves choosing the forecasting method judged most appropriate of the available methods and applying it to some specific situations. The choice of a method depends upon the characteristics of the series and the type of application. The rationale behind such an approach is the notion that a “best” method exists and can be identified. Further that the “best” method for the past will continue to be the best for the future. An alternative to the traditional approach is to aggregate information from different forecasting methods by aggregating forecasts. This eliminates the problem of having to select a single method and rely exclusively on its forecasts.

scholarly journals Production, Replenishment and Inventory Policies for Perishable Products in a Two-Echelon Distribution Network

2020 ◽  
Vol 12 (11) ◽  
pp. 4735
Author(s):  
Mingyuan Wei ◽  
Hao Guan ◽  
Yunhan Liu ◽  
Benhe Gao ◽  
Canrong Zhang
Keyword(s):  
Inventory Management ◽  
Valid Inequalities ◽  
Distribution Network ◽  
Planning Horizon ◽  
Branch And Cut ◽  
Computational Time ◽  
Perishable Products ◽  
Inventory Cost ◽  
Routing Problem ◽  
Selection Of

The research on production, delivery and inventory strategies for perishable products in a two-echelon distribution network integrates the production routing problem (PRP) and two-echelon vehicle routing problem (2E-VRP), which mainly considers the inventory and delivery sustainability of perishable products. The problem investigated in this study is an extension of the basic problems, and it simultaneously optimizes production, replenishment, inventory, and routing decisions for perishable products that will deteriorate over the planning horizon. Additionally, the lead time has been considered in the replenishment echelon, and the unit inventory cost varying with the inventory time is considered in the inventory management. Based on a newly designed model, different inventory strategies are discussed in this study: old first (OF) and fresh first (FF) strategies both for the first echelon and second echelon, for which four propositions to model them are proposed. Then, four valid inequalities, including logical inequalities, a ( ℓ , S , W W ) inequality, and a replenishment-related inequality, are proposed to construct a branch-and-cut algorithm. The computational experiments are conducted to test the efficiency of valid inequalities, branch-and-cut, and policies. Experimental results show that the valid inequalities can effectively increase the relaxed lower bound by 4.80% on average and the branch-and-cut algorithm can significantly reduce the computational time by 58.18% on average when compared to CPLEX in small and medium-sized cases. For the selection of strategy combinations, OF–FF is suggested to be used in priority.

Nonlinear Models Used to Analyze the Relation between Inflation and Unemployment

2020 ◽  
Vol 11 (2) ◽  
pp. 667
Author(s):  
Laura UNGUREANU ◽  
Madalina CONSTANTINESCU ◽  
Cristina POPÎRLAN
Keyword(s):  
Neural Networks ◽  
Mathematical Models ◽  
Nonlinear Models ◽  
Numerical Data ◽  
Optimization Models ◽  
Numerical Application ◽  
Forecasting Methods ◽  
Nonlinear Forecasting ◽  
The Relationship

Many mathematical models have been developed in the last years in order to analyze economic phenomena and processes. Some of these models are optimization models, static or dynamic, while others are developed specially to study the evolution of economic phenomena. The topic of this paper is forecasting with nonlinear models. A few well-known nonlinear models are introduced, and their properties are discussed. The variety of nonlinear relationships is important both from the perspective of estimation and from the precision of forecasts in the medium and especially long term. Most nonlinear forecasting methods and all methods based on neural networks lead to predictions that have a better quality than the forecasts obtained by linear methods. The last section of this paper contains a detailed study of the relationship between inflation and unemployment and a numerical application with numerical data from Romania.

scholarly journals Advising an Appropriate Forecasting Method for a Snacks Item (Biscuit) Manufacture Company in Bangladesh

2018 ◽  
Vol 66 (1) ◽  
pp. 55-58
Author(s):  
Nandita Barman ◽  
M Babul Hasan ◽  
Md Nayan Dhali
Keyword(s):  
Time Series ◽  
Inventory Management ◽  
Linear Trend ◽  
Exponential Smoothing ◽  
Demand And Supply ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Short Term Forecasting ◽  
Exponential Smoothing Method ◽  
Manufacture Company

In this paper, we study the most appropriate short-term forecasting methods for the newly launched biscuit factory produces different types of biscuits. One of them is nut-orange twisted biscuits. As it is a newly launched biscuit factory, it does not use any scientific method to find future demand of their products to produce for the purpose of sales. Having an error free production as well as a good inventory management we try to find an appropriate forecasting method for the sets of data we analyzed for that specific production. Several forecasting methods of time series forecasting such as the Moving Averages, Linear Regression with Time, Exponential Smoothing, Holt‘s Method, Holt-Winter‘s Method etc. can be applied to estimate the demand and supply for these companies. This paper focuses on selecting an appropriate forecasting technique for the newly launched biscuit company. For this, we analyze Exponential Smoothing method as used to time series. We observe from the empirical results of the analysis that if the data has no trend as well as seasonality, Exponential Smoothing Forecasting Method processes as the most appropriate forecasting method for the factory. If the data experiences linear trend in it then Holt’s Forecasting Method processes as the most appropriate forecasting method for the sets of data we analyzed. Dhaka Univ. J. Sci. 66(1): 55-58, 2018 (January)

scholarly journals A review and reflection on inventory management of perishable products in a single-echelon model

2018 ◽  
Vol 31 (3) ◽  
pp. 313
Author(s):  
Lincoln C. Wood ◽  
William Y.C. Wang ◽  
Linh Nguyen Khanh Duong
Keyword(s):  
Inventory Management ◽  
Perishable Products

Discrete Event Simulation in Inventory Management

2019 ◽  
pp. 977-988
Author(s):  
Linh Nguyen Khanh Duong ◽  
Lincoln C. Wood
Keyword(s):  
Inventory Management ◽  
Discrete Event ◽  
Simulation Models ◽  
Uncertain Demand ◽  
Perishable Products ◽  
Chain Management ◽  
Perishable Inventory ◽  
Event Simulation ◽  
Multiple Products ◽  
Alternative Product

Perishability and substitutability are two key attributes that cannot be ignored in supply chain management. Once produced, perishable products have a finite shelf life. When expired, they are either partially or wholly value-less. The more time that perishable inventory is in storage, the less time it is available for sale to customers. Product substitution is a possibility when considering multiple products. Research indicates that an alternative product is willingly chosen by customers if the preferred one is out of stock. Managers must decide on the replenishment time and replenishment quantity for each item within product subcategory to maximize expected profits under uncertain demand while minimizing the instances of running out of inventory (i.e., a stock out). The combination of these factors often requires simulation models to be developed to understand the behavior of the system as the parameters change. Simulation can incorporate stochasticity and complexity while providing detailed output for further analysis and optimization work.

An economic order interval-based simulation model for perishable products

2021 ◽  
Author(s):  
Roberto Montanari, ◽  
Eleonora Bottani ◽  
Andrea Volpi ◽  
Federico Solari ◽  
Giorgia Scozzesi
Keyword(s):  
Inventory Management ◽  
Economic Order ◽  
Perishable Products ◽  
Order Interval ◽  
Simulation Approach ◽  
Optimal Parameters ◽  
Inventory Policy ◽  
Total Inventory ◽  
Inventory Control Model ◽  
Realistic Data

The aim of this paper is to develop a model for reproducing an Economic Order Interval (EOI)-based inventory control model for perishable products. After a description of the model, a simulation approach is developed and used for determining the optimal parameters of the inventory policy, as well as the relationships between them and the numerical values that can minimize the total inventory management cost, thus making the system as efficient as possible. A numerical example, with realistic data, is proposed for showing the application of the model and its effectiveness for the identification of the optimal inventory policy parameters.

Inventory Management for distributors of perishable products

2017 ◽  
Vol 35 (1) ◽  
pp. 219-239 ◽  
Author(s):  
John Willmer Escobar ◽  
◽  
Rodrigo Linfati ◽  
Wilson Adarme Jaimes ◽  
◽  
...  
Keyword(s):  
Inventory Management ◽  
Perishable Products
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