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Combined simulated annealing algorithm for the discrete facility location problem.

Jin Qin1, Ling-Lin Ni, Feng Shi

  • 1School of Traffic and Transportation Engineering, Central South University, Changsha, China. csu qinjin@hotmail.com

Thescientificworldjournal
|October 11, 2012
PubMed
Summary
This summary is machine-generated.

A new combined simulated annealing (CSA) algorithm effectively solves the discrete facility location problem (DFLP). This two-layer method optimizes facility placement and customer demand allocation, outperforming existing algorithms.

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Area of Science:

  • Operations Research
  • Computer Science
  • Optimization

Background:

  • The discrete facility location problem (DFLP) is a critical challenge in logistics and operations.
  • Existing algorithms for DFLP face limitations in efficiency and solution quality.

Purpose of the Study:

  • To introduce and evaluate a novel algorithm for the discrete facility location problem.
  • To enhance the optimization of facility location and customer demand allocation.

Main Methods:

  • Development of a two-layer algorithm: combined simulated annealing (CSA).
  • External subalgorithm for facility location optimization.
  • Internal subalgorithm for customer demand allocation optimization.

Main Results:

  • The CSA algorithm demonstrated superior performance across 30 diverse DFLP instances.
  • CSA significantly outperformed previous algorithms in computational tests.
  • The algorithm provides a viable and effective alternative solution method for DFLP.

Conclusions:

  • The combined simulated annealing (CSA) algorithm is a highly effective approach for the discrete facility location problem.
  • CSA offers a significant improvement over existing methods, providing better solutions.
  • This research presents a valuable new tool for DFLP optimization.