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This paper presents an efficient procedure to extend dynamic lot-sizing heuristics that has been overlooked by inventory management literature and practice. Its intention is to show that the extension improves the results of basic heuristics significantly. We first present a comprehensive description of the extension procedure and then test its per...
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Context 1
... the case of erratic demand, the results of our study show that higher pp-values lead to higher cost variances, except employing LUC, compare therefore Figure 3. Regarding LBH, the results show that average pp-values lead to the highest cost variances. ...
Context 2
... can observe a tendency that high variance in order cycle ranges may lead to high total costs variance. However, as can be seen for LUC (pp ≤ 2500) in Figures 3 and 4, for example, a low order cycle range variance may result in high total cost variance. The results in Figure 4 also show that the LBH exten- sion algorithm generates longer order cycle ranges that are then closer to the results of WW compared to the results of the basic heuristics. ...
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... Features include computational set-up, the number of products simultaneously considered (single or multiple items), the production system levels (single or multiple stages), capacities and different demand types. Diverse feature combinations can be found in the literature (Andriolo et al., 2014;Beck et al., 2015;Brahimi et al., 2017;. ...
... FOP). Dynamic lot sizing concepts such as Silver-Meal heuristics (SMH), Part Period Balancing (PPB), Least Unit Cost (LUC) and Groff (GMR) consider the cumulated forecasted demand throughout the entire time horizon to define optimal lot sizes (Beck et al., 2015;Brahimi et al., 2017). As time goes by and the production demand changes, plans may be adapted accordingly (Beck et al., 2015;Buschkühl et al., 2010). ...
... Dynamic lot sizing concepts such as Silver-Meal heuristics (SMH), Part Period Balancing (PPB), Least Unit Cost (LUC) and Groff (GMR) consider the cumulated forecasted demand throughout the entire time horizon to define optimal lot sizes (Beck et al., 2015;Brahimi et al., 2017). As time goes by and the production demand changes, plans may be adapted accordingly (Beck et al., 2015;Buschkühl et al., 2010). Dynamic models require a more complex computation compared to static lot sizing techniques (Florian et al., 1980). ...
There exists a wide range of optimization models in the Operations Management (OM) community to solve complex problems such as lot sizing. However, their practical performance is often criticized due to the complexity of implementation and insufficient applicability in real-world decision processes. These theory-driven approaches are either simple to compute, but only focus on single aspects of the decision without being able to capture the practical problem comprehensively, or are complex computational models with limited practicability. We apply a Design Science Research approach to resolve this issue and show how lot size decision-making models should be designed to thoroughly support managers. Our innovative model combines Discrete Event Simulation (DES) with OM methods and is developed and tested in a case study in the metal processing industry. Results reveal that the model is suitable to provide transparency about effects and a range of efficient solutions.
... It is the improvement of nLPC is the best performance under 100 conditions. Beck et al. (2015) propose a dynamic lot-sizing approach to inventory management using leinz-bossert-habenicht (LBH) method. Groff's rule (GR) and least unit cost (LUC) are applied in LBH and called LBH-LUC and LBH-GR, respectively. ...
The proper production plan plays an important role in the cashew nuts market enterprise in order to reduce cost. This study aims to find the optimal production plan for cashew nuts using ant lion optimization (ALO), symbiotic organisms search (SOS), particle swarm optimization (PSO) and artificial bee colony algorithm (ABC). The novel objective function is introduced in this study. Three input data set, including production cost, holding cost and inventory quantity are investigated. The experiment cases consist of the frequency of production cycle time in January, February and March, respectively. As a results, four algorithms are available to estimate not only the proper production plan of cashew nuts but also an ability in reducing the inventory and the holding costs. In summary, the ALO algorithm provides better predictive skill than others for the cashew nuts production plan with the lowest RMSE value of 0.0913.
... Thus, this study used the concept of single exponential smoothing (SES) prediction to solve the aforementioned problem [6,7]. In addition, to help optimize the number of items that must be ordered, the economic order quantity (EOQ) method [8,9] was also used. ...
An early warning system was developed to help identify stock status as early as possible. For performance to improve, there needs to be a feature to predict the amount of stock that must be provided and a feature to estimate when to buy goods. This research was conducted to improve the inventory early warning system and optimize the Reminder Block's performance in minimum stock settings. The models used in this study are the single exponential smoothing (SES) method for prediction and the economic order quantity (EOQ) model for determining the quantity. The research was conducted by analyzing the Reminder Block in the early warning system, identifying data needs, and implementing the SES and EOQ mathematical models into the Reminder Block. This research proposes a new Reminder Block that has been added to the SES and EOQ models. It is hoped that this study will help in obtaining accurate information about the time and quantity of repurchases for efficient inventory management.
... The algorithm then proceeds with the next order, where the new beginning period is period + 1 of the previous order and proceeds sequentially until the end of the planning horizon is reached. The underlying foundation of this heuristic is the principle of the EOQ model under which the optimal order quantity will be the same regardless of whether total costs or unit costs are considered (Beck et al., 2015). ...
This work considers a setting in which external distributors of animal pharmaceutical companies lack transparency with the companies and/or have poor data keeping standards, resulting in situations where unexpected stockouts and various other issues occur, putting lives at stake. The objective of this work is to find a simple but effective approach to improve distributors’ replenishment decisions which can yield yearly replenishment plans detailed to the month. The company would then offer its distributors to improve their operations in exchange for better and more timely data, a by-product being that the production requirements are known in advance. Lot-sizing heuristics are a choice category of techniques due to their simplicity and to their relation to production planning concepts. Using simulation, it was found that the least unit cost and Silver-Meal heuristics perform best across all product types tested. The periodic order quantity rule can also be used for more stable solutions in terms of ordering frequency without too much loss in performance. Compared to historical ordering patterns, cost savings to the extent of 30% or more are possible through the use of those heuristics.
... Wagner and Whitin (1958) first proposed the exact formulation and solution methods for the dynamic lot sizing problem; their initial work was improved by Zabel (1964) and Bahl and Taj (1991). Researchers also investigated heuristics algorithms for dynamic lot sizing problems such as Silver and Meal (1973;1978), Kian et al. (2014) and Beck et al. (2015). ...
The aim of stochastic inventory control is to determine the timing of issuing replenishment order and the corresponding order quantity subject to uncertainty of demand and/or other system parameters. In this literature survey we focus on the single-item single-stocking location stochastic inventory control problem. More specifically, we survey exact and heuristic models under stationary and non-stationary demand according to uncertainty strategies proposed by Bookbinder and Tan (1988).
... Pengelolaan persediaan menentukan ukuran ekonomis dengan menyeimbangkan jumlah persediaan dan biaya pemesanannya dengan tujuan memberikan tingkat layanan tinggi dan biaya total minimal (Beck et al., 2015). Dengan pengelolaan bahan baku yang tepat bisa menjadi langkah efektif dalam mengurangi biaya penyimpanan (Moridipour dan Mousavi, 2014). ...
A large amount of inventory in the company makes high inventory cost, while low inventory will risk the occurrence of shortage of inventory. The research was conducted at Barjaz Company, to find out how the raw material inventory system applied by the company, and whether the system is efficient or not. Methods of data collection is done by conducting interviews to parties related to inventory and observation on the object under study. Data analysis techniques used are; EOQ analysis, determining safety stock, determining reorder point, determining maximum inventory, calculating inventory turnover and calculating total inventory cost. The results show that the inventory system applied today is still not effective. Companies should conduct inventory control system using EOQ method. With the implementation of EOQ, the company's inventory turnover value increased and the company issued a total inventory cost of Rp 1,099,982, lower than the company's inventory control system at Rp 1,671,100.
... Production scheduling has a significant impact on stock especially when multiple items are on production line. Thus, the integrated problem of DLSP with scheduling has been taken in analysis by Beck et al. (2015), Robinson et al. (2009) and Staggemeier and Clark (2001). Incentives are also used often in DLSP problems. ...
... Meta-heuristics are also widely applied in DLSP and Jans and Degraeve (2007) review them and make a comparison among these heuristics. Beck et al. (2015) review the Wagner-Whitin algorithm and provide an extension for dynamic lot sizing heuristics including Least unit cost, Groff's rule, Leinz-Bossert-Habenicht. ...
This thesis introduces a demand postponement policy in order to improve the performance of inventory management under batch ordering, advance demand information, capacitated/ uncapacitated and periodic/continuous review inventory systems. The main aim of this study is to find integrated demand postponement and inventory policies. The structure of the thesis consists of five main chapters which starts with an introduction in Chapter 1 which summarizes the main objectives of the study with a background information, followed by a Chapter 2 presenting an overview of the relevant literature and the methodology. Chapter 3 as the first research paper, an inventory problem with stochastic demand and batch ordering and lost sales based on a real case is introduced and a demand postponement policy applied on this system to convert some of the lost sales to advance demand. A Markov Decision Process model is proposed and it is solved through Linear Programming (LP). The dual of the primal model is used to reduce the computational effort and it is tested with several numerical data sets. The optimal inventory policy and discount policy for different batches are shown for managerial insights. In Chapter 4, the same problem without batch ordering is formulated by Markov Decision Process (MDP) solved by Backward induction algorithm. In addition, the demand pattern is changed to Advance Demand Information (ADI) which combines both stochastic and deterministic demand. The properties of optimal inventory and postponement policy parameters are analyzed and the numerical experiments are carried out under the uncapacitated and capacitated systems to show the impact of the postponement policy. The comparison of policy parameters with the literature shows that the demand postponement policy is highly effective for the efficient use of capacity. In Chapter 5, the extension of the problem to a continuous review inventory system with distribution strategies is studied by an Net Present Value (NPV) approach. The effectiveness of demand postponement under different financial settings are examined and an extensive numerical experiments are presented. The thesis ends with a conclusion in Chapter 6 including the summary of the results, limitations of the study and further research directions.
... Two meta-heuristicsgenetic algorithm and Hopfield neural network -are established for the dynamic lot-sizing problem. In recent years many other global publications have dealt with the lot-sizing problem, which has recently been solved by heuristics [20][21][22][23][24][25]. ...
The purpose of this article is to verify the possibility of using artificial neural networks (ANN) in business management processes, primarily in the area of supply chain management. The author has designed several neural network models featuring different architectures to optimize the level of the company’s inventory. The results of the research show that ANN can be used for managing a company’s order cycle and lead to reduced levels of goods purchased and storage costs. Optimal neural networks show suitable results for subsequent prediction of the amount of items to be ordered and for achieving reduced inventory purchase and keeping costs down.
... The common objective of lot-sizing decisions is the minimization of total costs by determining economic production quantities that balance inventory holding, setup and other affected costs (cf. Beck et al. 2015). ...
One aspect that has mostly been overlooked in traditional economic lot-sizing is the implication of decisions on manual tasks and workload. Although lot-sizing decisions can have a significant impact on required manual material handling and on human performance, works that consider ergonomic aspects in lot-sizing are rare. This paper presents a model that integrates ergonomic aspect in terms of human energy expenditure and rest allowance in a traditional lot-sizing model. The behavior of the model is analyzed in a numerical study, showing its ability to reflect manual workload, and that ergonomic aspects should be considered in lot-sizing decisions.
