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HA-CCP: A Hybrid Algorithm for Solving Capacitated Clustering Problem.

Yaoyao Liu1, Ping Guo1,2, Yi Zeng1,2

  • 1College of Computer Science, Chongqing University, Chongqing 400044, China.

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This study introduces HA-CCP, a novel hybrid algorithm for the capacitated clustering problem (CCP). HA-CCP offers improved efficiency and solution stability for this NP-hard optimization challenge.

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Area of Science:

  • Operations Research
  • Computer Science
  • Discrete Mathematics

Background:

  • The capacitated clustering problem (CCP) is an NP-hard optimization problem with significant engineering applications.
  • Existing heuristic algorithms like GRASP and VNS have shown success in solving CCP.
  • There is a need for improved algorithms to enhance efficiency and solution quality for CCP.

Purpose of the Study:

  • To develop a novel hybrid algorithm, HA-CCP, for solving the capacitated clustering problem.
  • To enhance the efficiency and solution quality of CCP algorithms.
  • To address stricter capacity constraints in CCP.

Main Methods:

  • A new hybrid algorithm, HA-CCP, is proposed.
  • HA-CCP incorporates a feasible solution construction method adapted for strict capacity bounds.
  • An adaptive local solution destruction and reconstruction method is employed to boost population diversity and convergence.

Main Results:

  • HA-CCP demonstrated superior performance on 58 out of 90 tested instances compared to existing algorithms.
  • The proposed algorithm achieved better average solution quality and stability.
  • HA-CCP exhibited superior average solving efficiency across various problem instances.

Conclusions:

  • HA-CCP represents a significant advancement in solving the capacitated clustering problem.
  • The algorithm's design effectively handles complex constraints and improves convergence.
  • HA-CCP offers a more stable and efficient approach for CCP applications.