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A modified artificial bee colony algorithm for p-center problems.

Alkın Yurtkuran1, Erdal Emel1

  • 1Department of Industrial Engineering, Uludag University, Görükle Campus, 16059 Bursa, Turkey.

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This study introduces an enhanced artificial bee colony (ABC) algorithm to efficiently solve the p-center problem, minimizing maximum distances in networks. The modified ABC algorithm demonstrates superior performance compared to existing methods.

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Area of Science:

  • Operations Research
  • Computer Science
  • Artificial Intelligence

Background:

  • The p-center problem aims to minimize the maximum distance from any network node to its closest facility.
  • Meta-heuristic algorithms, like the artificial bee colony (ABC) algorithm, are used for complex optimization problems.
  • Balancing exploration and exploitation is crucial for effective meta-heuristic performance.

Purpose of the Study:

  • To develop a modified artificial bee colony (ABC) algorithm for solving the p-center problem.
  • To enhance the ABC algorithm's search strategies for improved exploration and exploitation.
  • To effectively apply random key-based coding schemes within the ABC framework for the p-center problem.

Main Methods:

  • A modified artificial bee colony (ABC) algorithm incorporating diverse search strategies.
  • Utilization of random key-based coding schemes for problem representation.
  • Comparative analysis against state-of-the-art techniques on benchmark datasets.

Main Results:

  • The proposed modified ABC algorithm demonstrates high efficiency in solving the p-center problem.
  • Computational results show competitive or superior performance compared to existing methods.
  • The integration of varied search strategies effectively balances exploration and exploitation.

Conclusions:

  • The modified ABC algorithm with random key coding is an efficient approach for the p-center problem.
  • The enhanced search strategies contribute to the algorithm's effectiveness.
  • This method offers a promising alternative for network facility location optimization.