This chapter proposes a fuzzy approach to forecasting using a financial data set. The methodology used is multiple objective linear programming (MOLP). Selecting an individual forecast based on a single objective may not make the best use of available information for a variety of reasons. Combined forecasts may provide a better fit with respect to a single objective than any individual forecast. We incorporate soft constraints and preemptive additive weights into a mathematical programming approach to improve our forecasting accuracy. We compare the results of our approach with the preemptive MOLP approach. A financial example is used to illustrate the efficacy of the proposed forecasting methodology.
Lawrence, K.D., Pai, D.R. and Lawrence, S.M. (2010), "Forecasting using fuzzy multiple objective linear programming", Lawrence, K.D. and Klimberg, R.K. (Ed.) Advances in Business and Management Forecasting (Advances in Business and Management Forecasting, Vol. 7), Emerald Group Publishing Limited, Bingley, pp. 149-156. https://doi.org/10.1108/S1477-4070(2010)0000007013Download as .RIS
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