Heterogeneous component multiplicative error models for forecasting trading volumes

Naimoli, Antonio; Storti, Giuseppe

doi:10.1016/j.ijforecast.2019.06.002

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…Multiplicative Decomposition Forecasting is used to identify demand with seasonal types (Naimoli & Storti, 2019). This forecasting method uses a seasonal index based on the seasonal Period to identify future demand levels.…”

Section: Methodsmentioning

confidence: 99%

Smart Production Planning Model for T-Shirt Products at Raensa Convection

Santosa¹,

Hidayat²,

Siskandar³

et al. 2023

JITI

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The increasing stock condition of cotton combed 30s t-shirts causes Convection to require optimal production planning, influenced by demand, safety stock, and selling price. The analysis of forecasting demand for t-shirts obtained a need for 217 t-shirts using the Multiplicative Decomposition forecasting method with MAD = 22.47 and MAPE = 0.17. Based on demand data for 1 year, the Safety Stock that must be maintained is 126 shirts/month or 3 shirts/week. The optimal production defuzzification results are 369 t-shirts with 81 fuzzy rules used. The Master Production Planning (MPS) directs the production schedule to be carried out in January, scheduled for the 4th week of December the previous year, as many as 123 shirts and ended on the third Sunday in January as many as 92 shirts to maintain stock conditions and meet the demand of consumer.

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Section: Methodsmentioning

confidence: 99%