Demand forecast process planning with fuzzy logic support
DOI:
https://doi.org/10.32358/rpd.2015.v1.89Keywords:
Demand Forecasting, Classic Decomposition, Fuzzy Logic.Abstract
Generally, demand forecast is a crucial part of demand management process. As in many cases production cannot be of the make-to order type, it becomes necessary how many products will be sold. In this scenario, minimizing sales forecasting error should be the top priority in any company. In order to attain this goal, two techniques are presented here: Classic Decomposition and Forecast based on Fuzzy Logic. The main result is the low error found when applying both techniques, with a slight advantage for the latter.Downloads
References
AROZO, R. Sales and Operations Planning: Uma maneira de obter ganhos com integração interna. COPPEAD, 2000.
DU, X. F., LEUNG, S. C. H., ZHANG, J. L., LAI, K.K. Demand forecasting of perishable farm products using support vector machine. International journal of systems Science. v. 44, n. 3, p. 556-567, mar. 2013.
FERREIRA, B. B. Aplicação de Ferramentas de Lógica Nebulosa à Predição de Séries Temporais. Rio de Janeiro: Instituto Militar de Engenharia, Curso de Mestrado em Engenharia Mecânica, Dissertação, 2008. 124 p.
FIRJAN. Série de dados utilizados na previsão. Disponível em: <http://www.firjan.org.br/data/pages/4028808120E98EC7012122BA8A14346E.htm>. Acesso em: 2011.
LAMBERT, D. M. Supply Chain Management: Processes, Partnerships, Performance. 2. ed. Florida, SCMI, 2004.
LIN, C.C., LIN, C.L., SHYU, J. Z. Hybrid multi-model forecasting system: a case study on display market. Knowledge-based systems. v. 71, p. 279-289, nov. 2014.
LIU, N., REN, S., CHOI, T. M., HUI, C. L., NG, S. F. Sales Forecasting for Fashion Retailing Service Industry: A Review. Mathematical Problems in Engineering. v. 2013, Article ID 738675, 9 p., 2013. doi:10.1155/2013/738675
LINARES-MUTARÓS, S. MERINGÓ, J. M. FERRER-COMELAT, J. C. Processing extreme values in sales forecasting. Cybernetics and Systems. v. 46, n. 3-4, p. 207-229, mai. 2015.
LUSTOSA, L. J.; MESQUITA, M. A.; GONÇALVES, O. L.; OLIVEIRA, R. J. Planejamento e Controle da Produção. 1. ed. Rio de Janeiro: Elsevier, 2008.
MORETTIN, P. A.; TOLOI, C. M. Séries Temporais. São Paulo: Atual, 1986.
SAVI, M. A. Dinâmica Não-Linear e Caos. 1. ed. Rio de Janeiro: E-papers Serviços Editoriais Ltda, 2006.
TANSCHEIT, R. Sistemas Fuzzy, Departamento de Engenharia Elétrica, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro. 2004.
WANKE, P.; JULIANELLI, L. Previsão de vendas: processos organizacionais e métodos quantitativos e qualitativos. 2. ed. São Paulo: Atlas, 2011.
WANG, L. X., MENDEL, J. M. Generating Fuzzy Rules by Learning from Examples, IEEE Trans. On Systems, Man and Cybernetics, , V 22, n. 6, p.1414-1427 1992.
XIA, M. WONG, W. K. A seasonal discrete grey forecasting model for fashion retailing. Journal knowledge-based systems. V. 57, p. 119-126, Fev. 2014.
YIN, R. Estudos de Caso: Planejamento e Métodos. 2. ed. Porto Alegre: Bookman, 2010.
ZADEH, L. “Fuzzy Sets”, Information and Control, vol. 8, p. 338-353, 1965.
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