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Related Experiment Videos

Recourse-based facility-location problems in hybrid uncertain environment.

Shuming Wang1, Junzo Watada, Witold Pedrycz

  • 1Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan. smwangips@gmail.com

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|December 4, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel two-stage fuzzy-random facility-location model with recourse (FR-FLMR) to address complex hybrid uncertain environments. A hybrid optimization algorithm (MBACO) demonstrates superior performance in solving these challenging facility-location problems.

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Area of Science:

  • Operations Research
  • Optimization Theory
  • Applied Mathematics

Background:

  • Facility-location problems are critical in logistics and supply chain management.
  • Real-world scenarios often involve hybrid uncertainty, combining randomness and fuzziness.
  • Existing models struggle with the complexity of fuzzy-random variables in facility-location decisions.

Purpose of the Study:

  • To develop a robust model for facility-location problems under hybrid uncertainty.
  • To propose an effective computational method for solving the developed model.
  • To evaluate the performance of the proposed method against existing algorithms.

Main Methods:

  • Development of a two-stage fuzzy-random facility-location model with recourse (FR-FLMR).
  • Introduction of a fuzzy-random simulation technique to compute the recourse function.
  • Proposal of a hybrid mutation-based binary ant-colony optimization (MBACO) approach integrating simulation and simplex algorithm.

Main Results:

  • The study derives bounds for the optimal objective value of the FR-FLMR.
  • Fuzzy-random simulation is shown to be a viable method for computing the recourse function.
  • The hybrid MBACO algorithm outperforms other discrete metaheuristics in finding optimal solutions.

Conclusions:

  • The developed FR-FLMR effectively models facility-location problems in hybrid uncertain environments.
  • The hybrid MBACO approach provides an efficient and effective solution methodology.
  • This research offers a significant advancement in solving complex, uncertain optimization problems.