Forecasting using fuzzy multiple objective linear programming

Kenneth D. Lawrence, Dinesh R. Pai, Sheila M. Lawrence

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationAdvances in Business and Management Forecasting
EditorsKenneth Lawrence, Ronald Klimberg
Number of pages8
StatePublished - 2010

Publication series

NameAdvances in Business and Management Forecasting
ISSN (Print)1477-4070

All Science Journal Classification (ASJC) codes

  • General Business, Management and Accounting


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