An extension for dynamic lot-sizing heuristics

Beck, Fabian G.; Grosse, E. H.; Teßmann, Ruben

doi:10.1080/21693277.2014.985390

Cited by 7 publications

(4 citation statements)

References 41 publications

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“…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.…”

Section: An Optimal Production Plan For Cashew Nuts Community Enterpr...mentioning

confidence: 99%

An Optimal Production Plan for Cashew Nuts Community Enterprise Using Metaheuristic Algorithms

Phromfaiy¹,

Wangsoh²,

Surin³

2022

International Journal of Applied Metaheuristic Computing

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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.

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Section: An Optimal Production Plan For Cashew Nuts Community Enterpr...mentioning

confidence: 99%

An Optimal Production Plan for Cashew Nuts Community Enterprise Using Metaheuristic Algorithms

Phromfaiy¹,

Wangsoh²,

Surin³

2022

International Journal of Applied Metaheuristic Computing

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“…Penerapan metode EOQ dapat menentukan frekuensi pemesanan dan jumlah pesanan produk yang paling ekonomis sesuai dengan kebutuhan perusahaan. Oleh karena itu, pemesanan ekonomis ini akan membantu perusahaan untuk memberikan tingkat layanan yang tinggi dengan biaya total yang minimal (Beck et al, 2015). Hal yang diperhatikan dalam penerapan metode EOQ yaitu titik pemesanan ulang, waktu tunggu, dan juga persediaan pengaman."…”

Section: Pendahuluanunclassified

Analisis Kinerja Manajemen Persediaan Produk Ud. Sinar Jaya Karangasem

Sanjaya

Purnawati

2021

EJMUNUD

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Inventory plays an important role in the company's operational activities, it is necessary to do inventory management in order to minimize losses caused by the large inventory costs. This research is conducted at UD. Sinar Jaya, aims to determine the performance of product inventory management and whether it’s efficient or not. Research data are obtained through interviews and observations. Descriptive analysis technique is used, which describes systematically several stages starting with ABC analysis, EOQ calculation, safety stock calculation, re-order point calculation, maximum inventory calculation, inventory turnover calculation, and comparing the total inventory cost between the method applied by the company with the EOQ method. Results show that product inventory management performance is not efficient. This is indicated by the total cost of inventory incurred using the company method in 2019 amounting to IDR 43,058,137. The product inventory management system that should be carried out is to classify products with ABC analysis, then determine EOQ of 1,208 units, determine safety stock of 518 units, and determine the re-order point of 1,099 units for each classification at unit A, so that the total cost of inventory incurred is only IDR 32,716,517 or 24.02 % lower than the actual application of company methods. Keywords: ABC analysis, EOQ, inventory costs

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“…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].…”

Section: Literature Reviewmentioning

confidence: 99%

An Artificial Neural Network Model for a Wholesale Company's Order-Cycle Management

Šustrová

2016

International Journal of Engineering Business Management

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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.

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An extension for dynamic lot-sizing heuristics

Cited by 7 publications

References 41 publications

An Optimal Production Plan for Cashew Nuts Community Enterprise Using Metaheuristic Algorithms

An Optimal Production Plan for Cashew Nuts Community Enterprise Using Metaheuristic Algorithms

Analisis Kinerja Manajemen Persediaan Produk Ud. Sinar Jaya Karangasem

An Artificial Neural Network Model for a Wholesale Company's Order-Cycle Management

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