Forecasting using fuzzy multiple objective linear programming

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

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

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
Pages149-156
Number of pages8
DOIs
StatePublished - Dec 1 2010

Publication series

NameAdvances in Business and Management Forecasting
Volume7
ISSN (Print)1477-4070

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)

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