Research on demand forecasting of retail supply chain emergency logistics based on NRS-GA-SVM

2018 ◽  
Author(s):  
Hong Xue ◽  
Chi Jiang ◽  
Boyu Cai ◽  
Yi Yuan
Keyword(s):  
Supply Chain ◽  
Demand Forecasting ◽  
On Demand ◽  
Emergency Logistics

scholarly journals Demand forecasting and information platform in tourism

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 247-252 ◽  
Author(s):  
Yue Li ◽  
Qi-Jie Jiang
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Information Processing ◽  
Information Asymmetry ◽  
Demand Forecasting ◽  
Bullwhip Effect ◽  
Information Platform ◽  
On Demand ◽  
Processing Ability ◽  
Tourism Supply Chain

AbstractInformation asymmetry and the bullwhip effect have been serious problems in the tourism supply chain. Based on platform theory, this paper established a mathematical model to explore the inner mechanism of a platform’s influence on stakeholders’ ability to forecast demand in tourism. Results showed that the variance of stakeholders’ demand predictions with a platform was smaller than the variance without a platform, which meant that a platform would improve predictions of demand for stakeholders. The higher information-processing ability of the platform also had other effects on demand forecasting. Research on the inner logic of the platform’s influence on stakeholders has important theoretical and realistic value. This area is worthy of further study.

scholarly journals A Comprehensive Study on Demand Forecasting Methods and Algorithms for Retail Industries

2021 ◽  
Vol 23 (06) ◽  
pp. 409-420
Author(s):  
Udbhav Vikas ◽  
◽  
Karthik Sunil ◽  
Rohini S. Hallikar ◽  
Pattem Deeksha ◽  
...  
Keyword(s):  
Machine Learning ◽  
Supply Chain ◽  
Demand Forecasting ◽  
Performance Comparison ◽  
Supply Side ◽  
Learning Approaches ◽  
Time Series Regression ◽  
On Demand ◽  
Forecasting Methods ◽  
Comprehensive Study

Without a doubt, demand forecasting is an essential part of a company’s supply chain. It predicts future demand and specifies the level of supply-side readiness needed to satisfy the demand. It is imperative that if a company’s forecasting isn’t reasonably reliable, the entire supply chain suffers. Over or under forecasted demand would have a debilitating impact on the operation of the supply chain, along with planning and logistics. Having acknowledged the importance of demand forecasting, one must look into the techniques and algorithms commonly employed to predict demand. Data mining, statistical modeling, and machine learning approaches are used to extract insights from existing datasets and are used to anticipate unobserved or unknown occurrences in statistical forecasting. In this paper, the performance comparison of various forecasting techniques, time series, regression, and machine learning approaches are discussed, and the suitability of algorithms for different data patterns is examined.

Modeling and analysis of the on-demand spare parts supply using additive manufacturing

2019 ◽  
Vol 25 (3) ◽  
pp. 473-487 ◽  
Author(s):  
Yuan Zhang ◽  
Stefan Jedeck ◽  
Li Yang ◽  
Lihui Bai
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Spare Parts ◽  
Production Optimization ◽  
Arrival Process ◽  
Powder Bed Fusion ◽  
Content Type ◽  
Modeling And Analysis ◽  
Powder Bed ◽  
On Demand

PurposeDespite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.Design/methodology/approachIn this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.FindingsThe simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.Originality/valueThe findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

scholarly journals Coordinating Pricing and Advertising Decisions for Supply Chain under Consignment Contract in the Dynamic Setting

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhihui Wu ◽  
Lichao Feng ◽  
Dongyan Chen
Keyword(s):  
Supply Chain ◽  
Differential Game ◽  
Optimal Strategies ◽  
Feasible Region ◽  
Comparison Analysis ◽  
On Demand ◽  
Dynamic Setting ◽  
State Dependent ◽  
Differential Game Theory ◽  
Advertising Effort

In this paper, via the differential game method, the problems of the pricing and advertising decision are investigated by considering the effect of number of the platform users on demand. In addition, a novel contract is developed to coordinate the supply chain. Firstly, the optimal strategies of the pricing and advertising are given in the decentralized and centralized scenarios by applying the differential game theory. Also, the comparison analysis concerning on the optimal strategies is proposed in two decision scenarios. It is shown that the centralized scenario could lead to the higher advertising effort of each member and a lower retail price. Next, we construct the state-dependent contract with hope to coordinate the supply chain and then improve the performance of the supply chain. Finally, a numerical example is provided to illustrate the impacts of the price-elasticity index of demand and the effectiveness of the number of retailer’s platform users onto the feasible region of the corresponding contract.

scholarly journals The impact of implementing a demand forecasting system into a low-income country's supply chain

Vaccine ◽  
2016 ◽  
Vol 34 (32) ◽  
pp. 3663-3669 ◽  
Author(s):  
Leslie E. Mueller ◽  
Leila A. Haidari ◽  
Angela R. Wateska ◽  
Roslyn J. Phillips ◽  
Michelle M. Schmitz ◽  
...  
Keyword(s):  
Supply Chain ◽  
Low Income ◽  
Demand Forecasting ◽  
Forecasting System ◽  
The Impact

SCCS - A Supply Chian Collaboration Service

2011 ◽  
Vol 48-49 ◽  
pp. 1002-1005
Author(s):  
Hui Ping Lin ◽  
Xu Wei Zhu ◽  
Wei Ping Li ◽  
Li Liu ◽  
Zhao Hui Xie
Keyword(s):  
Supply Chain ◽  
Service Oriented Architecture ◽  
Low Cost ◽  
Supply Chain Performance ◽  
Supply Chain Collaboration ◽  
Business Partners ◽  
On Demand ◽  
Flexible Support ◽  
Business Application ◽  
Service Oriented

This paper presents a supply chain collaboration service (SCCS) in SaaS paradigm to support inter-organization interaction between business partners. SaaS is very attractive to enterprises because it offers low cost and flexible on-demand IT solution. The paper presents an extensible service oriented architecture that can integrate business application as a service into SCCS. In order to improve the supply chain performance, it provides flexible support for information sharing between business partners. The SCCS prototype has been developed.

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