On flexible product-mix decision problems under randomness and fuzziness

Takashi Hasuike, Hiroaki Ishii

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

This paper considers several models of product-mix decision problems and production planning problems under uncertain conditions, and shows that these are extensional and versatile models for resolving previous product-mix problems. These proposed models include randomness derived from statistical analysis based on historical data, ambiguity of decision maker's intuition and the quality of received information, and flexibility in accomplishing the original plan. Furthermore, given that the upper limit values of some constraints have flexibility, and given a decision maker's level of satisfaction, we propose a flexible product mix of problems using the theory of constraints (TOC), and develop an efficient solution method. We then provide a numerical example that compares our models with some previous basic models. Efficiency of flexibility is obtained when our proposed models are applied to several conditions, such as measurable changes from the expected value of future returns.

Original languageEnglish
Pages (from-to)770-787
Number of pages18
JournalOmega
Volume37
Issue number4
DOIs
Publication statusPublished - 2009 Aug
Externally publishedYes

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Keywords

  • Flexible product-mix decision problem
  • Level of satisfaction of decision maker
  • Stochastic and fuzzy programming
  • Theory of constraints

ASJC Scopus subject areas

  • Strategy and Management
  • Information Systems and Management
  • Management Science and Operations Research

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