A study on behaviour of bullwhip effect in (R, S) inventory control system considering DWT-MGGP demand forecasting model

Purpose The purpose of this paper is to propose a forecasting model to predict the demand under uncertain environment to control the bullwhip effect (BWE) considering review-period order-up-to level ((R, S)) inventory control policy and its different variants such as (R, βS) (R, γO) and (R, γO, βS) proposed by Jakšič and Rusjan, (2008) and Bandyopadhyay and Bhattacharya (2013). Design/methodology/approach A hybrid forecasting model has been developed by combining the feature of discrete wavelet transformation (DWT) and an intelligence technique, multi-gene genetic programming (MGGP), denoted as DWT-MGGP. Performance of DWT-MGGP model has been verified under (R, S) inventory control policy considering demand from three different manufacturing companies. Findings A comparison between DWT-MGGP model and autoregressive integrated moving average forecasting model has been done by estimating forecast error and BWE. Further, this study has been extended with analysing the behaviour of BWE considering different variants of (R, S) policy such as (R,βS) (R, γO) and (R,γO,βS) and found that BWE can be moderated by controlling the inventory smoothing (β) and order smoothing parameters (γ). Research limitations/implications This study is limited to different variants of (R, S) inventory control policy. However, this study can be further extended to continuous review policy. Practical implications The proposed DWT-MGGP model can be used as a suitable demand forecasting model to control the BWE when (R, S), (R,βS) (R,γO) and (R,γO,βS)inventory control policies are followed for replenishment. Originality/value This study analyses the behavior of BWE through controlling the inventory smoothing (β) and order smoothing parameters (γ) when demand is predicted using DWT-MGGP forecasting model and order is estimated using (R, S), (R,βS) (R,γO) and (R,γO,βS) inventory control policies.

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Analisis Bullwhip Effect pada Rantai Supply dengan Model Q Menggunakan Pendekatan Hadley-Within di PT. XYZ Medan

Talenta Conference Series Energy and Engineering (EE) ◽

10.32734/ee.v2i4.688 ◽

2019 ◽

Vol 2 (4) ◽

Author(s):

Martha Purnama Sari Panggabean ◽

Dimas Akmarul Putera ◽

Nursafwah

Keyword(s):

Supply Chain ◽

Inventory Control ◽

Distribution System ◽

Control Policy ◽

Bullwhip Effect ◽

Product Distribution ◽

Soft Drinks ◽

Inventory Cost ◽

Inventory Control Policy ◽

Q Model

PT. XYZ adalah perusahaan yang bergerak didalam pembuatan kemasan botol minum. Pendistribusian produk dilakukan PT XYZ menggunakan data historis berdasarkan jumlah permintaan pada tahun 2013 dan 2014. Data tersebut menunjukkan bahwa terjadinya perbedaan hasil. Tahun 2013 memiliki jumlah permintaan yang lebih rendah dari tahun 2014. Informasi terdapat bahwa perlu dilakukan pengevaluasian karena didalam rantai produksi terdapat bullwhip effect. Terdapat nilai bullwhip Effect menujukan bahwa nilai bullwhip effect untuk distributor Indomaret, Carrefour, dan rantai manufakturnya masing-masing sebesar 0,5303; 0,2967, dan 0,5114. Usulan perbaikan dapat diatasi yaitu dengan model Q yang berfungsi menggendalikan persediaan pada rantai pasok dengan metodeHadley-Within. Perhitungan pengendalian persediaan untuk distributor Indomaret, Carrefour, dan rantai manufakturnya masing-masing sebesar 1,0721; 1,100; dan 1,0714. Hasil dari perhitungan menujukan bahwa terjadi keseimbangan antara penjual dan pembeli sehingga biaya pun dapat dihematkan pada PT XYZ. PT. XYZ Medan is manufacturing company that produce soft drinks of beverages in containers. In the product distribution system at PT. XYZ Medan, found that the number of orders based on the result of forecasting in 2013 lower than actual orders at distrbutor and manufacturer in 2014. Distorsion of information on this order can evaluate the indication of bullwhip effect in supply chain. Based on the result calculation of bullwhip effect, found that the value of bullwhip effect for Indomaret distributor, Carrefour, and supply chain of manufacturer each of 0,5303; 0,2967, and 0,5114. Proposed improvements to predominate bullwhip effect that is by doing inventory control policy with Q model using Hadley-Within approach. The value of bullwhip effect aftre doing inventory control policy for Indomaret distributor, Carrefour, and supply chain of manufacturer each of 1,0721; 1,100; dan 1,0714. The value of bullwhip effect which is close to one shows that the variance between the number of the order and the number of the demand nearly balanced so as to save the inventory cost at PT. XYZ Medan.

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Logistics demand forecasting model based on improved neural network algorithm

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189479 ◽

2020 ◽

pp. 1-11

Author(s):

Hongjiang Ma ◽

Xu Luo

Keyword(s):

Neural Network ◽

Influencing Factor ◽

Demand Forecasting ◽

Forecasting Model ◽

Logistics System ◽

Model Based ◽

Network Algorithm ◽

Neural Network Algorithm ◽

Demand Forecasting Model ◽

Logistics Demand

The irrationality between the procurement and distribution of the logistics system increases unnecessary circulation links and greatly reduces logistics efficiency, which not only causes a waste of transportation resources, but also increases logistics costs. In order to improve the operation efficiency of the logistics system, based on the improved neural network algorithm, this paper combines the logistic regression algorithm to construct a logistics demand forecasting model based on the improved neural network algorithm. Moreover, according to the characteristics of the complexity of the data in the data mining task itself, this article optimizes the ladder network structure, and combines its supervisory decision-making part with the shallow network to make the model more suitable for logistics demand forecasting. In addition, this paper analyzes the performance of the model based on examples and uses the grey relational analysis method to give the degree of correlation between each influencing factor and logistics demand. The research results show that the model constructed in this paper is reasonable and can be analyzed from a practical perspective.

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