A global forecasting support system adapted to textile distribution

Thomassey, Sébastien; Happiette, M.; Castelain, J. M.

doi:10.1016/j.ijpe.2004.03.001

Cited by 47 publications

(21 citation statements)

References 24 publications

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“…A large number of sales forecasting papers have been reported, which involves a wide variety of real-world applications in numerous industries, mainly including print circuit board industry (Chang et al 2005;Hadavandi et al 2011), tourism and lodging industry (Andrew et al 1990;Smith et al 1994;Kulendran and Wong 2011), airline industry (Oberhausen and Koppelman 1982;Saab and Zouein 2001;Lin 2006;Jing et al 2010), foodservice industry (Miller et al 1991;Chen and Ou 2009;Tsai and Kimes 2009), and apparel industry (Sztandera et al 2004;Thomassey et al 2005;Au et al 2008;Guo et al 2013). Danese and Kalchschmidt (2011) examined the impact of multivariate forecasting on companies' performance by analyzing the sample data from 343 manufacturing companies in six different countries.…”

Section: Sales Forecastingmentioning

confidence: 99%

New Developments and Decision-makings in Production and Retailing

Guo¹

2016

Intelligent Decision-Making Models for Production and Retail Operations

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This chapter introduces firstly the new developments in production and retail operations. These developments bring new challenges to daily operations and decision-makings because some new decision-making problems and problem features emerge and have to be handled. This chapter then reviews previous studies on decision-making problems in production and retailing, including production planning, production scheduling, assembly line balancing, and sales forecasting. Finally, this chapter reviews commonly used techniques for typical decision-making problems, including production optimization and sales forecasting.

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Section: Sales Forecastingmentioning

confidence: 99%

New Developments and Decision-makings in Production and Retailing

Guo¹

2016

Intelligent Decision-Making Models for Production and Retail Operations

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“…Compared to the existing products forecasting, prediction on new product forecasting seems to be much more complicated and difficult, due to the absence of historical sales data. In the current literature, some papers study the new item forecasting (e.g., [60][61][62][63][64]), but very few papers explore the new item forecasting in fashion industry, and exceptions include the following: (i) an item classification method is used in [12], a neural networks and classification combined method is reported in [41], and a fuzzy and Holt Winter hybrid method is examined in [33], and an ANN based hybrid method is proposed in [37]. Obviously, the AI method is used frequently for new item forecasting.…”

Section: Applications In Fashion Industrymentioning

confidence: 99%

Sales Forecasting for Fashion Retailing Service Industry: A Review

Liu

Ren

Choi

et al. 2013

Mathematical Problems in Engineering

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Sales forecasting is crucial for many retail operations. It is especially critical for the fashion retailing service industry in which product demand is very volatile and product's life cycle is short. This paper conducts a comprehensive literature review and selects a set of papers in the literature on fashion retail sales forecasting. The advantages and the drawbacks of different kinds of analytical methods for fashion retail sales forecasting are examined. The evolution of the respective forecasting methods over the past 15 years is revealed. Issues related to real-world applications of the fashion retail sales forecasting models and important future research directions are discussed.

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“…They found out that the SOM/CBR is more accurate and efficient when being applied to the forecast of the data than K/CBR or traditional CBR. Thomassey, Happiette, and Castelain (2005) proposed a hybrid sales forecasting model based on fuzzy logic, neural networks and evolutionary procedures, permitting the processing of uncertain data. The experimental results showed that the performance of the hybrid model was superior to other models such as ARMAX.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%