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Related Concept Videos

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Related Experiment Videos

Minimum risk facility location-allocation problem with type-2 fuzzy variables.

Xuejie Bai1, Ying Liu2

  • 1College of Science, Agricultural University of Hebei, Baoding, Hebei 071001, China.

Thescientificworldjournal
|April 30, 2014
PubMed
Summary

This study addresses facility location decisions under uncertainty by using fuzzy programming. It develops a novel method to optimize location and allocation plans, improving model applicability and decision-making.

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Area of Science:

  • Operations Research
  • Management Science
  • Decision Analysis

Background:

  • Facility location decisions are long-term strategic choices.
  • Uncertainty in transportation costs and customer demand impacts these decisions.
  • Existing models struggle with the complexity of type-2 fuzzy facility location-allocation (FLA) problems.

Purpose of the Study:

  • To examine the impact of uncertain parameters on optimal facility location and allocation.
  • To formulate the FLA problem as a fuzzy minimum risk programming model using type-2 fuzzy variables.
  • To develop an effective method for solving complex type-2 fuzzy FLA problems.

Main Methods:

  • Formulation of the FLA problem as type-2 fuzzy minimum risk programming.
  • Derivation of a critical value formula for type-2 triangular fuzzy variables.
  • Conversion of the fuzzy FLA model to an equivalent parametric mixed integer programming form.
  • Design of a parameter decomposition method for optimization.

Main Results:

  • A novel method to solve type-2 fuzzy FLA problems was developed.
  • The proposed method converts fuzzy models into solvable parametric mixed integer programs.
  • A numerical example demonstrated the model's significance and the method's effectiveness.

Conclusions:

  • The developed parametric optimization method is credible and superior for facility location-allocation problems with uncertainty.
  • The approach enhances the applicability of facility location models by accounting for parameter uncertainty.
  • This research provides a robust framework for strategic facility location decisions.